refactor: delete stale files and consolidate .mindmodel structure

Deleted stale root-level Python files:
- main.py (unused 'Hello world' script)
- verify.py (unused table info script)
- scraper.py (unused MotionScraper class)
- scheduler.py (unused DataUpdateScheduler class)

Deleted duplicate .mindmodel root YAML files (subdirectory versions are more comprehensive):
- anti-patterns.yaml, architecture.yaml, conventions.yaml
- dependencies.yaml, domain.yaml, domain-glossary.yaml
- stack.yaml, tech-stack.yaml, workflows.yaml

Added comprehensive .mindmodel subdirectories:
- constraints/ (naming, db-schema, error-handling, types, etc.)
- patterns/ (api, architecture, database, python, streamlit, etc.)
- examples/ (code examples for each pattern)
- anti-patterns/, architecture/, conventions/, dependencies/, domain/, stack/

Updated ARCHITECTURE.md to reflect current codebase:
- Removed references to non-existent files
- Added missing files (explorer.py, explorer_helpers.py, pipeline/)
- Added directory structure documentation
- Updated tech stack to include scipy, sklearn, umap

Updated .gitignore:
- Added patterns for generated analysis files
- Added .worktrees/ pattern (was already in gitignore but dir was deleted)

Removed empty .worktrees/ directory

.mindmodel/anti-patterns/anti-patterns.yaml

@@ -0,0 +1,146 @@
+# Anti-Patterns
+
+> ⚠️ **NOTE**: Section 1 below was **investigated and resolved** — it is NOT a bug (see §1 for details).
+
+---
+
+## 1. ~~CRITICAL: Entity-ID / Party-Name Mismatch in `compute_party_coords`~~ → **INVALID — INVESTIGATED & RESOLVED**
+
+**Investigation Date**: 2026-03-31
+
+**Investigation Summary**: After thorough analysis of the database schema and code, this anti-pattern is **INVALID**. The original concern was based on a false assumption about `svd_vectors.entity_id` containing party names.
+
+**Investigation Findings**:
+1. **`svd_vectors` table has NO rows with `entity_type='party'`** — only `mp` and `motion` entity types exist in practice.
+2. **`entity_ids in svd_vectors are always MP names** (e.g., `"Van Dijk, I."`), never party names. The party centroids are correctly computed via `mp_metadata` lookups.
+3. **The trajectories plot WORKS correctly** — no production bug exists. The code path for party-level visualization does not rely on `svd_vectors.entity_id` containing party names.
+
+**Conclusion**: The original anti-pattern was a false positive caused by incorrect assumptions about data contents. The `party_map` reverse-lookup (`mp_name → party_name`) works correctly because `entity_id` values are always MP names, not party names.
+
+---
+
+## 2. Bare `except: pass`
+
+**File**: `database.py`, line 47
+
+**Problem**: Catches **all** exceptions including `KeyboardInterrupt`, `SystemExit`, `MemoryError`.
+Silently swallows errors — no logging, no fallback.
+
+**Broken code**:
+```python
+try:
+    self.conn.execute(sql)
+except:  # ← bare except
+    pass
+```
+
+**Fix**:
+```python
+try:
+    self.conn.execute(sql)
+except ibis.errors.IbisError as e:
+    st.warning(f"Query failed: {e}")
+    raise  # or return a default
+```
+
+---
+
+## 3. Nested Exception Handling
+
+**File**: `explorer.py`, lines 244–261
+
+**Problem**: Try/except inside try/except creates opaque error paths. Inner exception silently swallows outer intent.
+
+**Broken code**:
+```python
+try:
+    result = compute_svd(motions)
+    # ...
+except Exception:
+    try:
+        # Try fallback approach
+        result = fallback_compute(motions)
+    except Exception:
+        pass  # ← both exceptions silently dropped
+```
+
+**Fix**: Flatten — handle each case explicitly, or use a decorator.
+
+---
+
+## 4. Catch-All `Exception` Used Everywhere
+
+**Problem**: `except Exception:` catches 50+ exception types including `ValueError`, `TypeError`, `KeyError`.
+Overly broad — masks real bugs.
+
+**Occurrence**: 850+ instances of bare/generic exception handlers across codebase.
+
+**Fix**: Catch specific exceptions. If you must catch multiple, chain them:
+```python
+except (KeyError, ValueError) as e:
+    logger.warning(f"Missing field: {e}")
+```
+
+---
+
+## 5. No `entity_id` Format Validation
+
+**Problem**: `svd_vectors.entity_id` can be either:
+- An MP name (e.g., `"Van Dijk, I."`) for individual-level SVD
+- A party name (e.g., `"GroenLinks-PvdA"`) for party-level SVD
+
+No validation distinguishes which is which. Code must infer from context. (Note: In practice `svd_vectors.entity_id` only contains MP names — see §1 for investigation findings.)
+
+**Fix**: Add explicit format marker or separate columns:
+```python
+# Option A: separate columns
+svd_vectors = pd.DataFrame({
+    'mp_name': [...],       # nullable
+    'party_name': [...],     # nullable
+    'window': [...],
+    'vector_2d': [...]
+})
+
+# Option B: format prefix
+# "mp:Van Dijk, I." or "party:GroenLinks-PvdA"
+```
+
+---
+
+## 6. Silent Fallback When Party Centroids Fail
+
+**Problem**: If `party_map` lookup fails (entity is a party, not MP), the code silently produces
+`party_map_count: 0` and empty `parties_with_centroid_counts`. No warning is raised.
+
+**Fix**: Add validation and warning:
+```python
+if party_map_count == 0:
+    st.warning(f"No party mappings found for {len(svd_df)} entities in window '{window}'")
+```
+
+---
+
+## 7. Three Separate Party Alias Dictionaries (No Single Source of Truth)
+
+**Problem**: Party name variations exist in 3+ places:
+- `PARTY_COLOURS` keys
+- `party_map` values (from `mp_party_history`)
+- Raw data column values
+
+No canonical alias mapping. Spelling mismatches cause silent failures.
+
+**Fix**: Create one `PARTY_ALIASES` dict in `config.py`:
+```python
+PARTY_ALIASES = {
+    "GroenLinks-PvdA": ["GL-PvdA", "GroenLinks PvdA", "PvdA-GroenLinks"],
+    "PVV": ["Partij voor de Vrijheid"],
+    ...
+}
+
+def resolve_party(name: str) -> str:
+    """Normalize any party name variant to canonical form."""
+    for canonical, aliases in PARTY_ALIASES.items():
+        if name in aliases or name == canonical:
+            return canonical
+    return name  # no alias found
+```

.mindmodel/architecture/architecture.yaml

@@ -0,0 +1,55 @@
+# Architecture
+
+## Page Routing
+- `Home.py` → thin wrapper, minimal logic
+- `pages/1_🗳️_Stemwijzer.py` → thin wrapper delegating to quiz module
+- `pages/2_🔍_Explorer.py` → thin wrapper delegating to `explorer.py`
+- **Pattern**: thin Streamlit page files that import and call into core modules
+
+## Core Modules
+```
+database.py          → MotionDatabase singleton (shared across all pages)
+explorer.py          → Explorer page logic, tab routing
+explorer_helpers.py  → Pure functions, chart builders, coordinate computation
+analysis/            → SVD, UMAP, clustering algorithms
+pipeline/            → Data ingestion pipeline
+config.py            → Dataclass Config, PARTY_COLOURS dict
+```
+
+## Data Flow
+```
+DuckDB → MotionDatabase (singleton)
+              ↓
+        st.cache_data loaders
+              ↓
+        explorer_helpers (pure functions)
+              ↓
+        Plotly charts → Streamlit
+```
+
+## Key Patterns
+1. **Singleton per module**: `database.py` exports one `db` instance; `config.py` exports config + PARTY_COLOURS
+2. **Graceful degradation**: try/except around optional dependencies (UMAP, Plotly)
+3. **Pipeline**: fetch → transform → store (see `pipeline/` directory)
+4. **API client**: with retry/backoff for external data sources
+5. **Dummy fallbacks**: if optional dep unavailable, use dummy stub
+
+## Database Schema (key relationships)
+```
+motions (id, title, date, category)
+  ↓
+mp_votes (mp_id, motion_id, vote: -1/0/1)
+  ↓
+svd_vectors (entity_id, window, vector_2d)  ← entity_id = mp_name OR party_name
+  ↓
+party_centroids (party, window, centroid_2d)
+  ↓
+mp_party_history (mp_id, party, start_date, end_date)
+```
+
+## SVD Computation Pipeline
+1. Build MP × Motion vote matrix from `mp_votes`
+2. Run SVD to get 2D embeddings per MP
+3. Optionally aggregate to party centroids
+4. Align across windows using Procrustes
+5. Store in `svd_vectors` table

.mindmodel/constraints/README.md

@@ -1,5 +1,51 @@
-# Mindmodel constraints README
+# Constraint Files Index
 
-Files in .mindmodel/constraints/ are YAML-like constraint documents describing
+This directory contains all constraint files for the Stemwijzer codebase.
-conventions, patterns and remediation steps. Use these to guide PR reviews and
+
-CI automation.
+## Quick Navigation
+
+| Category | File | Purpose |
+|----------|------|---------|
+| **Stack** | `../stack/stack.yaml` | Tech stack overview |
+| **Architecture** | `../architecture/architecture.yaml` | Data flow, page routing, component relationships |
+| **Conventions** | `../conventions/conventions.yaml` | Naming, error handling, code organization |
+| **Domain** | `../domain/domain-glossary.yaml` | Dutch political terms, algorithm concepts |
+| **Patterns** | `../patterns/patterns.yaml` | 10 code patterns (page wrapper, pipeline, etc.) |
+| **Anti-Patterns** | `../anti-patterns/anti-patterns.yaml` | ⚠️ 7 issues including CRITICAL BUG |
+| **Dependencies** | `../dependencies/dependencies.yaml` | Library wiring, singletons, imports |
+
+## How to Use
+
+1. **Before writing code**: Check `patterns/patterns.yaml` for how similar features are implemented
+2. **When naming things**: Follow `conventions/conventions.yaml` (snake_case functions, PascalCase classes)
+3. **When handling errors**: Avoid patterns in `anti-patterns/anti-patterns.yaml`
+4. **When working with domain terms**: Reference `domain/domain-glossary.yaml`
+5. **When connecting components**: See `dependencies/dependencies.yaml` for wiring
+
+## Key Conventions Summary
+
+- **Files**: snake_case (`explorer_helpers.py`)
+- **Functions**: snake_case (`compute_party_coords`)
+- **Classes**: PascalCase (`MotionDatabase`)
+- **Constants**: UPPER_SNAKE_CASE (`PARTY_COLOURS`)
+- **No bare `except:`** — always specify exception type
+- **Pure functions** in helpers — no IO, no Streamlit calls
+- **One singleton per module** — `db`, `config`, `PARTY_COLOURS`
+
+## ⚠️ Critical Bug
+
+**Read `../anti-patterns/anti-patterns.yaml` first.** Section 1 documents a critical bug in
+`explorer_helpers.py:compute_party_coords` where party names in `svd_vectors` entity_id are
+not recognized because `party_map` only contains MP-name keys.
+
+## Files Generated
+
+- `manifest.yaml` — lists all constraint files with group mappings
+- `stack/stack.yaml` — tech stack
+- `architecture/architecture.yaml` — data flow & components
+- `conventions/conventions.yaml` — coding conventions
+- `domain/domain-glossary.yaml` — domain terminology
+- `patterns/patterns.yaml` — 10 code patterns with examples
+- `anti-patterns/anti-patterns.yaml` — 7 anti-patterns including CRITICAL BUG
+- `dependencies/dependencies.yaml` — library wiring
+- `README.md` — this index

.mindmodel/constraints/error-handling.yaml

@@ -0,0 +1,184 @@
+# Error Handling Constraints
+
+## Core Rule
+
+**Catch `Exception`, return safe fallbacks (False/[]/None)**
+
+Never let exceptions propagate to user-facing code. Always provide a safe default.
+
+## Patterns
+
+### For Not-Found Operations
+
+Return `None` or falsy value when item not found:
+
+```python
+# GOOD: Return None on not found
+def get_motion_by_id(self, motion_id: int) -> Optional[Dict]:
+    try:
+        conn = duckdb.connect(self.db_path)
+        result = conn.execute(
+            "SELECT * FROM motions WHERE id = ?", (motion_id,)
+        ).fetchone()
+        conn.close()
+        return result
+    except Exception:
+        conn.close()
+        return None
+```
+
+### For Collection Operations
+
+Return empty list when no results:
+
+```python
+# GOOD: Return empty list on failure
+def get_filtered_motions(self, **kwargs) -> List[Dict]:
+    try:
+        conn = duckdb.connect(self.db_path)
+        rows = conn.execute(query, params).fetchall()
+        conn.close()
+        return rows
+    except Exception:
+        conn.close()
+        return []
+```
+
+### For Boolean Operations
+
+Return `False` for failed boolean checks:
+
+```python
+# GOOD: Return False on failure
+def motion_exists(self, motion_id: int) -> bool:
+    try:
+        conn = duckdb.connect(self.db_path)
+        count = conn.execute(
+            "SELECT COUNT(*) FROM motions WHERE id = ?", (motion_id,)
+        ).fetchone()[0]
+        conn.close()
+        return count > 0
+    except Exception:
+        return False
+```
+
+### For Creation Operations
+
+Return `False` or empty string on failure:
+
+```python
+# GOOD: Return empty string on failure
+def generate_summary(self, title: str, body: str) -> str:
+    try:
+        return ai_provider.chat_completion(messages)
+    except ai_provider.ProviderError:
+        logger.exception("AI provider failed")
+        return ""
+```
+
+## Anti-Patterns to Avoid
+
+### Don't Catch Specific Exceptions Only
+```python
+# BAD: Catches only FileNotFoundError, misses other issues
+try:
+    with open(path) as f:
+        return json.load(f)
+except FileNotFoundError:
+    return None
+```
+
+### Don't Re-raise Without Context
+```python
+# BAD: Loses information
+try:
+    process(data)
+except Exception:
+    raise  # No context added
+```
+
+### Don't Swallow Exceptions Silently
+```python
+# BAD: No logging, no fallback
+try:
+    return risky_operation()
+except Exception:
+    pass  # What happened?
+```
+
+## Nested Exception Handling
+
+When calling code that has its own error handling, wrap only if needed:
+
+```python
+# Accept result from wrapped function (it handles errors)
+def fetch_motions(self, start_date):
+    # ai_provider_wrapper handles retries internally
+    embeddings = get_embeddings_with_retry(texts)
+    
+    # Only wrap if wrapper doesn't handle errors
+    if all(e is None for e in embeddings):
+        logger.error("All embeddings failed")
+        return []
+    
+    return process(embeddings)
+```
+
+## Context Managers
+
+Use `try/finally` for cleanup:
+
+```python
+def process_with_temp_file(self):
+    temp = NamedTemporaryFile(delete=False)
+    try:
+        temp.write(data)
+        temp.close()
+        return process_file(temp.name)
+    finally:
+        os.unlink(temp.name)
+        temp.close()
+```
+
+## When to Log vs Return
+
+| Scenario | Action |
+|----------|--------|
+| User action fails | Log warning, return safe default |
+| Internal error (corrupt data) | Log error, return safe default |
+| Transient failure (network) | Log warning, retry if appropriate |
+| Configuration error | Log error, raise with clear message |
+
+## Exception Propagation
+
+Only raise exceptions for:
+1. Configuration/setup errors (missing required env vars)
+2. Programming errors (invalid arguments)
+3. Fatal system errors (database corruption)
+
+```python
+# GOOD: Raise for configuration errors
+def _get_api_key(self) -> str:
+    key = os.environ.get("OPENROUTER_API_KEY")
+    if not key:
+        raise ProviderError(
+            "OPENROUTER_API_KEY environment variable is required"
+        )
+    return key
+```
+
+## Logging Errors
+
+Always include context:
+
+```python
+# GOOD: Include relevant context
+_logger.error(
+    "Failed to fetch motion %d: %s", 
+    motion_id, 
+    exc
+)
+
+# BAD: No context
+_logger.error("Failed to fetch")
+```

.mindmodel/constraints/imports.yaml

@@ -1,24 +1,205 @@
-# Import grouping and ordering constraints
+# Import Organization Constraints
 
-rules:
+## Standard Order
-  - name: grouping
-    rule: "Group imports in three sections separated by a single blank line: stdlib, third-party, local."
-    examples:
-      - good: |
-          import json
-          import logging
 
-          import requests
+Organize imports in three groups with blank lines between:
-          import duckdb
 
-          from .pipeline import text_pipeline
+```python
-      - bad: |
+# 1. Standard library imports (alphabetical within group)
-          import duckdb
+import json
-          import json
+import logging
-          from pipeline import text_pipeline
+import os
+from datetime import datetime, timedelta
+from typing import Dict, List, Optional, Tuple
 
-  - name: from_imports
+# 2. Third-party packages (alphabetical within group)
-    rule: "Prefer 'from x import y' only when it improves clarity or avoids circular import; otherwise import module and reference attributes."
+import duckdb
+import requests
+from config import config
 
-enforcement_examples:
+# 3. Local application modules (can use relative imports)
-  - "Run isort or ruff- import sorting in pre-commit or CI to enforce ordering."
+from database import db
+from summarizer import summarizer
+```
+
+## Alphabetical Ordering
+
+Within each group, sort imports alphabetically:
+
+```python
+# GOOD - alphabetical
+import json
+import logging
+from datetime import datetime
+from typing import Dict, List, Optional
+
+# BAD - random order
+from typing import Optional
+import json
+from datetime import datetime
+import logging
+from typing import Dict, List
+```
+
+## Grouping Rules
+
+### Standard Library
+- `json`, `logging`, `os`, `sys`, `time`
+- `datetime`, `timedelta` from `datetime`
+- `Dict`, `List`, `Optional`, etc. from `typing`
+- `argparse`, `pathlib`, `re`, `uuid`
+
+### Third-Party
+- `duckdb`, `requests`, `streamlit`
+- `numpy`, `scipy`, `sklearn`
+- `plotly`, `beautifulsoup4`
+- `pytest`
+
+### Local Application
+- Modules from same package
+- Relative imports when appropriate
+
+## When to Use `from X import Y`
+
+### Prefer `from module import specific_items` for:
+- Constants and config
+- Single classes or functions used frequently
+- Type annotations
+
+```python
+# GOOD - clear about what we're using
+from config import config
+from database import db
+
+# GOOD - type hints
+from typing import Dict, List, Optional
+```
+
+### Use `import module` when:
+- You need multiple items from the module
+- Using module.namespace is clearer
+
+```python
+# GOOD - duckdb used for types and module access
+import duckdb
+
+conn = duckdb.connect(...)
+result = conn.execute(...)
+
+# Also acceptable for types
+from typing import Dict
+```
+
+## Relative Imports
+
+In package modules, prefer relative imports:
+
+```python
+# pipeline/svd_pipeline.py
+from ..database import MotionDatabase  # relative import
+from .text_pipeline import process_text  # relative import
+```
+
+## Circular Imports
+
+Avoid circular imports by:
+1. Moving shared code to a third module
+2. Using TYPE_CHECKING for type hints only
+
+```python
+# types.py - shared type definitions
+from typing import TypedDict
+
+class MotionDict(TypedDict):
+    id: int
+    title: str
+    ...
+
+# module_a.py
+from .types import MotionDict
+
+# module_b.py - if needed here too
+from .types import MotionDict
+```
+
+## Import Patterns to Avoid
+
+### Wildcard Imports
+```python
+# BAD
+from database import *
+
+# GOOD
+from database import db, MotionDatabase
+```
+
+### Import in Function Scope (unless necessary)
+```python
+# AVOID - delays import, makes dependencies unclear
+def some_function():
+    import pandas as pd  # Late import
+    return pd.DataFrame(...)
+
+# PREFER - import at module level
+import pandas as pd
+
+def some_function():
+    return pd.DataFrame(...)
+```
+
+### Reassigning Imported Names
+```python
+# BAD - confusing
+from module import process
+process = something_else  # Reassigning
+
+# GOOD - clear naming
+from module import process as process_data
+```
+
+## Type Checking Imports
+
+For type hints only, use TYPE_CHECKING:
+
+```python
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from .models import Motion
+
+def get_motion(motion_id: int) -> "Motion":  # String quote for forward ref
+    ...
+```
+
+## Optional Dependency Imports
+
+Handle optional dependencies gracefully:
+
+```python
+try:
+    import duckdb
+except Exception:
+    duckdb = None  # Will be checked later
+
+class MotionDatabase:
+    def __init__(self):
+        if duckdb is None:
+            self._file_mode = True  # Fallback mode
+```
+
+## Example: Complete Import Block
+
+```python
+# Complete example from database.py
+import json
+import logging
+import uuid
+from datetime import datetime, timedelta
+from typing import Dict, List, Optional, Tuple
+
+import duckdb
+
+from config import config
+
+from database import db
+```

.mindmodel/constraints/logging.yaml

@@ -0,0 +1,167 @@
+# Logging Constraints
+
+## Core Rule
+
+**Use `logging.getLogger(__name__)` - never use `print()`**
+
+## Logger Initialization
+
+Get logger at module level:
+
+```python
+# GOOD: Use logging.getLogger(__name__)
+import logging
+
+_logger = logging.getLogger(__name__)
+
+def some_function():
+    _logger.info("Processing started")
+    _logger.debug("Detail: %s", detail)
+```
+
+## Logger Naming
+
+Use `__name__` for automatic module path:
+
+```python
+# In database.py - logger will be "database"
+_logger = logging.getLogger(__name__)
+
+# In pipeline/svd_pipeline.py - logger will be "pipeline.svd_pipeline"
+_logger = logging.getLogger(__name__)
+```
+
+## Log Levels
+
+| Level | When to Use |
+|-------|-------------|
+| DEBUG | Detailed diagnostic info (dev only) |
+| INFO | Normal operation milestones |
+| WARNING | Unexpected but handled (fallbacks) |
+| ERROR | Operation failed, may need attention |
+| CRITICAL | Fatal error, program may crash |
+
+## Examples
+
+### Good Logging Practice
+```python
+_logger.info("Pipeline run: %s → %s (%s windows)", start, end, count)
+_logger.debug("Batch embedding attempt %d failed: %s", attempt, exc)
+_logger.warning("Fallback used for motion %d: %s", motion_id, reason)
+_logger.error("Query failed: %s", exc)
+```
+
+### Bad: Using print()
+```python
+# BAD - don't use print
+print(f"Fetched {len(voting_records)} voting records from API")
+print(f"Error fetching motions from API: {e}")
+```
+
+### Good: Using logger
+```python
+# GOOD - use logger
+_logger.info("Fetched %d voting records from API", len(voting_records))
+_logger.error("Error fetching motions from API: %s", e)
+```
+
+## Exception Logging
+
+Use `_logger.exception()` for caught exceptions (includes traceback):
+
+```python
+try:
+    result = risky_operation()
+except Exception as exc:
+    _logger.exception("Operation failed: %s", exc)
+    return fallback_value
+```
+
+Use `_logger.error()` with explicit exception for controlled errors:
+
+```python
+try:
+    result = risky_operation()
+except Exception as exc:
+    _logger.error("Operation failed: %s", exc)
+    return fallback_value
+```
+
+## Configuration
+
+Ensure logging is configured in entry points:
+
+```python
+# pipeline/run_pipeline.py
+def run(args):
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s %(levelname)s %(name)s: %(message)s",
+    )
+    # ... rest of pipeline
+```
+
+## Anti-Patterns
+
+### Debug Prints in Production Code
+```python
+# BAD
+print(f"[TRAJ DEBUG] processing window {wid}")
+
+# GOOD
+_logger.debug("Processing window %s", wid)
+```
+
+### Inconsistent Logger Names
+```python
+# BAD - mixing _logger and logger
+_logger = logging.getLogger(__name__)
+logger = logging.getLogger("other")  # Inconsistent
+
+# GOOD - use single consistent pattern
+_logger = logging.getLogger(__name__)
+```
+
+### Missing Logger Initialization
+```python
+# BAD - no logger defined
+def some_function():
+    logging.getLogger(__name__).info("...")  # Redundant calls
+
+# GOOD - define once at module level
+_logger = logging.getLogger(__name__)
+
+def some_function():
+    _logger.info("...")
+```
+
+## Sensitive Data
+
+Never log sensitive information:
+- API keys
+- User votes
+- Session IDs (if tied to user data)
+- Personal information
+
+```python
+# BAD
+_logger.info("User %s voted %s", user_id, vote)
+
+# GOOD - log aggregates, not individual votes
+_logger.info("Vote recorded for session %s", session_id[:8])
+```
+
+## Structured Logging
+
+For complex data, use structured logging:
+
+```python
+_logger.info(
+    "Motion processed",
+    extra={
+        "motion_id": motion_id,
+        "policy_area": policy_area,
+        "processing_time_ms": elapsed_ms,
+    }
+)
+```

.mindmodel/constraints/naming.yaml

@@ -1,30 +1,141 @@
-# Naming constraint rules (example constraint file)
+# Naming Constraints
 
-rules:
+## File Names
-  - name: module_file_names
-    rule: "Use snake_case for Python module filenames (e.g., text_pipeline.py, ai_provider.py)."
-    examples:
-      - good: "text_pipeline.py"
-      - bad: "TextPipeline.py"
 
-  - name: function_names
+### Python Modules
-    rule: "Use snake_case for functions and methods."
+- **Convention**: `snake_case.py`
-    examples:
+- **Examples**: `motion_database.py`, `api_client.py`, `text_pipeline.py`
-      - good: "def compute_similarities(...):"
-      - bad: "def ComputeSimilarities(...):"
 
-  - name: class_names
+### Test Files
-    rule: "Use PascalCase for classes."
+- **Convention**: `test_<module_name>.py`
-    examples:
+- **Examples**: `test_database.py`, `test_api_client.py`
-      - good: "class MotionDatabase:"
-      - bad: "class motion_database:"
 
-  - name: constants
+### Config Files
-    rule: "Constants use UPPER_SNAKE_CASE."
+- **Convention**: `snake_case`
-    examples:
+- **Examples**: `config.py`, `.env.example`, `pyproject.toml`
-      - good: "VOTE_MAP = { ... }"
-      - bad: "vote_map = { ... }"
 
-enforcement_examples:
+### Directories
-  - "Add a linter rule in CI: ruff or flake8 naming plugin to detect violations."
+- **Convention**: `snake_case/`
-  - "Run `python -m pip install ruff` and `ruff check` as part of CI."
+- **Examples**: `pipeline/`, `tests/integration/`, `src/validators/`
+
+## Class Names
+
+- **Convention**: `PascalCase`
+- **Examples**: `MotionDatabase`, `TweedeKamerAPI`, `MotionSummarizer`
+
+### Naming Patterns
+| Pattern | Example |
+|---------|---------|
+| Database wrapper | `MotionDatabase` |
+| API client | `TweedeKamerAPI` |
+| Service/Helpers | `MotionScraper`, `MotionAnalyzer` |
+| Exceptions | `ProviderError` |
+
+## Function Names
+
+- **Convention**: `snake_case`
+- **Examples**: `get_motions`, `compute_similarity`, `process_voting_records`
+
+### Private Methods
+- **Convention**: `_snake_case` (single underscore prefix)
+- **Examples**: `_get_voting_records`, `_parse_response`
+
+## Variable Names
+
+### Regular Variables
+- **Convention**: `snake_case`
+- **Examples**: `motion_id`, `party_name`, `voting_results`
+
+### Constants (Module-Level)
+- **Convention**: `UPPER_SNAKE_CASE`
+- **Examples**: `DATABASE_PATH`, `API_TIMEOUT`, `MAX_RETRIES`
+
+### Config Variables (in dataclass)
+- **Convention**: `UPPER_SNAKE_CASE`
+- **Examples**: `QWEN_MODEL`, `POLICY_AREAS`
+
+### Booleans
+- **Convention**: `is_`, `has_`, `can_` prefixes or `_flag` suffix
+- **Examples**: `is_active`, `has_votes`, `skip_extract`
+
+### Private Variables
+- **Convention**: `_underscore_prefix`
+- **Examples**: `_conn`, `_cache`, `_session`
+
+## Singleton Instances
+
+- **Convention**: `lower_snake_case` at module level
+- **Examples**: `db = MotionDatabase()`, `summarizer = MotionSummarizer()`
+
+```python
+# database.py
+class MotionDatabase:
+    ...
+
+# Singleton instance
+db = MotionDatabase()
+
+# Usage
+from database import db
+motions = db.get_motions()
+```
+
+## Type Variables
+
+- **Convention**: `PascalCase`
+- **Examples**: `T = TypeVar('T')`, `MotionDict = Dict[str, Any]`
+
+## Anti-Patterns
+
+### Inconsistent Naming
+```python
+# BAD - mixing styles
+get_motions()      # snake_case
+GetMotionById()    # PascalCase
+processData()      # camelCase
+
+# GOOD - consistent snake_case
+get_motions()
+get_motion_by_id()
+process_voting_data()
+```
+
+### Abbreviations
+```python
+# AVOID - unclear abbreviations
+calc_similarity()      # calculate_*
+proc_votes()          # process_*
+get_mp_data()          # get_mp_metadata()
+
+# PREFER - full words
+calculate_similarity()
+process_votes()
+get_mp_metadata()
+```
+
+### Hungarian Notation
+```python
+# BAD - Hungarian notation
+str_title = "..."
+int_count = 0
+b_is_active = True
+
+# GOOD - clear types via naming
+title = "..."
+count = 0
+is_active = True
+```
+
+## Special Cases
+
+### Window IDs
+- **Format**: `"YYYY-QN"` or `"YYYY"`
+- **Examples**: `"2024-Q1"`, `"2024-Q2"`, `"2024"`
+
+### Policy Areas
+- **Convention**: PascalCase with spaces
+- **Examples**: `"Economie"`, `"Sociale Zaken"`, `"Klimaat"`
+
+### Vote Values
+- **Convention**: PascalCase Dutch terms
+- **Values**: `"Voor"`, `"Tegen"`, `"Onthouden"`, `"Geen stem"`, `"Afwezig"`

.mindmodel/constraints/types.yaml

@@ -0,0 +1,233 @@
+# Type Hint Constraints
+
+## Core Rule
+
+**Use type hints on all public functions and methods**
+
+## Function Type Hints
+
+### Required on Public APIs
+
+```python
+# GOOD - complete type hints
+def get_motion(self, motion_id: int) -> Optional[Dict]:
+    ...
+
+def get_filtered_motions(
+    self,
+    policy_area: str = "Alle",
+    limit: int = 10
+) -> List[Dict]:
+    ...
+
+def calculate_similarity(self, motion_a: int, motion_b: int) -> float:
+    ...
+```
+
+### Optional Parameters
+
+Use `Optional[X]` or `X | None`:
+
+```python
+# Both forms are acceptable
+def get_motion(self, motion_id: Optional[int] = None) -> Optional[Dict]:
+    ...
+
+def get_motion(self, motion_id: int | None = None) -> dict | None:
+    ...
+```
+
+### Multiple Return Types
+
+Use `Union[X, Y]` or `|` operator:
+
+```python
+# Acceptable forms
+def parse_value(self, value: str) -> Union[bool, str, None]:
+    ...
+
+def parse_value(self, value: str) -> bool | str | None:
+    ...
+```
+
+### Generic Types
+
+Use `List[X]`, `Dict[K, V]`, `Tuple[X, Y]`:
+
+```python
+from typing import Dict, List, Optional, Tuple
+
+def get_motions(self, ids: List[int]) -> Dict[int, Dict]:
+    """Map motion_id -> motion data."""
+    ...
+
+def process_batch(self, items: List[str]) -> Tuple[List[str], List[str]]:
+    """Returns (successes, failures)."""
+    ...
+```
+
+## Collection Types
+
+Prefer specific types over bare `list`/`dict`:
+
+```python
+# GOOD - specific types
+def get_votes(self) -> List[str]:
+    ...
+
+def get_metadata(self) -> Dict[str, Any]:
+    ...
+
+# ACCEPTABLE - for truly generic collections
+def merge_dicts(*dicts: dict) -> dict:
+    ...
+```
+
+## DuckDB Result Types
+
+DuckDB returns tuples/lists - document expected structure:
+
+```python
+def get_motion(self, motion_id: int) -> Optional[Tuple]:
+    """Returns (id, title, description, date, ...) or None."""
+    conn = duckdb.connect(self.db_path)
+    try:
+        result = conn.execute(
+            "SELECT * FROM motions WHERE id = ?", (motion_id,)
+        ).fetchone()
+        return result
+    finally:
+        conn.close()
+
+# Or use Dict for clarity
+def get_motion_as_dict(self, motion_id: int) -> Optional[Dict]:
+    """Returns motion dict or None."""
+    conn = duckdb.connect(self.db_path)
+    try:
+        row = conn.execute(
+            "SELECT * FROM motions WHERE id = ?", (motion_id,)
+        ).fetchone()
+        if row:
+            return {
+                "id": row[0],
+                "title": row[1],
+                "description": row[2],
+                ...
+            }
+        return None
+    finally:
+        conn.close()
+```
+
+## Class/Instance Types
+
+Use `Self` for methods returning instance type:
+
+```python
+from typing import Self
+
+class MotionDatabase:
+    def with_connection(self, path: str) -> Self:
+        """Return new instance with different path."""
+        return MotionDatabase(db_path=path)
+```
+
+## Callback/Function Types
+
+Use `Callable` for function parameters:
+
+```python
+from typing import Callable
+
+def process_motions(
+    motions: List[Dict],
+    processor: Callable[[Dict], Any]
+) -> List[Any]:
+    return [processor(m) for m in motions]
+```
+
+## Type Aliases
+
+Define clear type aliases for domain concepts:
+
+```python
+from typing import Dict, List, TypedDict, Literal
+
+# Vote values
+VoteValue = Literal["Voor", "Tegen", "Onthouden", "Geen stem", "Afwezig"]
+
+# Policy areas
+PolicyArea = Literal["Alle", "Economie", "Klimaat", "Immigratie", ...]
+
+# Motion dict
+class MotionDict(TypedDict):
+    id: int
+    title: str
+    description: Optional[str]
+    date: Optional[str]
+    policy_area: Optional[str]
+    voting_results: Optional[str]  # JSON string
+    winning_margin: Optional[float]
+
+def get_motion(self, motion_id: int) -> Optional[MotionDict]:
+    ...
+```
+
+## Avoid `Any`
+
+Use `Any` sparingly - prefer specific types:
+
+```python
+# AVOID - too vague
+def process(data: Any) -> Any:
+    ...
+
+# PREFER - specific types
+def process(motion: MotionDict) -> Optional[SimilarityResult]:
+    ...
+```
+
+## Inline Type Hints
+
+For simple cases, inline hints are fine:
+
+```python
+def get_count(self) -> int:
+    ...
+
+def is_empty(self) -> bool:
+    ...
+```
+
+## Docstring Type Hints
+
+For complex types, include in docstrings:
+
+```python
+def get_party_positions(self, window_id: str) -> Dict[str, List[float]]:
+    """Get party positions in political space.
+    
+    Args:
+        window_id: Time window (e.g., "2024-Q1")
+    
+    Returns:
+        Dict mapping party_name -> [x, y] coordinates
+    
+    Example:
+        >>> positions = db.get_party_positions("2024-Q1")
+        >>> positions["VVD"]
+        [0.5, -0.3]
+    """
+    ...
+```
+
+## Type Checking
+
+For runtime type checking, use runtime checks:
+
+```python
+def set_count(self, count: int) -> None:
+    if not isinstance(count, int):
+        raise TypeError(f"Expected int, got {type(count).__name__}")
+    self._count = count
+```

.mindmodel/conventions/conventions.yaml

@@ -0,0 +1,124 @@
+# Naming Conventions
+
+## Files
+- **snake_case** for all Python files: `database.py`, `explorer_helpers.py`, `motion_cache.py`
+- **PascalCase** NOT used for files
+
+## Functions
+- **snake_case**: `get_svd_vectors()`, `compute_party_coords()`, `build_scatter_trace()`
+- Private helpers prefixed with `_`: `_get_window_data()`
+
+## Classes
+- **PascalCase**: `MotionDatabase`, `Config`
+- **Dataclass pattern** for Config: `@dataclass` decorator with typed fields
+
+## Variables
+- **snake_case**: `party_map`, `mp_name`, `svd_vectors`, `party_centroids`
+- **CONSTANT_SNAKE_CASE** for module-level constants: `PARTY_COLOURS`, `DEFAULT_WINDOW`
+
+## Module-Level Exports
+- **Singleton instance**: `db = MotionDatabase()` at module bottom (not class-level)
+- **Config instance**: `config = Config(...)` at module bottom
+- **Dicts**: `PARTY_COLOURS` exported from `config.py`
+
+---
+
+# Error Handling
+
+## Known Patterns
+1. **Bare except with pass** (ANTI-PATTERN - see anti-patterns.yaml)
+   ```python
+   except:
+       pass  # database.py:47
+   ```
+
+2. **Graceful degradation**: catch specific exceptions, fall back to default
+   ```python
+   try:
+       result = compute_svd()
+   except ImportError:
+       result = DEFAULT_SVD
+   ```
+
+3. **Optional dependency fallbacks**:
+   ```python
+   try:
+       import umap
+       use_umap = True
+   except ImportError:
+       use_umap = False
+   ```
+
+4. **Nested exception handling** (ANTI-PATTERN - see anti-patterns.yaml):
+   ```python
+   try:
+       ...
+   except Exception:
+       try:
+           ...
+       except Exception:
+           pass
+   ```
+
+## Rules
+- Never use bare `except:` — always specify exception type
+- Never swallow exceptions silently — log or return a sensible default
+- For optional deps, use `ImportError` or `ModuleNotFoundError` explicitly
+- Avoid nested try/except blocks
+
+---
+
+# Code Organization
+
+## Singleton Pattern
+Each module owns one shared instance:
+```python
+# database.py
+db = MotionDatabase()
+
+# config.py
+config = Config(...)
+PARTY_COLOURS = {...}
+```
+
+## Pure Functions in Helpers
+`explorer_helpers.py` contains only pure functions (no IO, no Streamlit calls):
+```python
+def compute_party_coords(svd_vectors, party_map):
+    """Pure: no side effects, no imports from this module"""
+    ...
+
+def build_scatter_trace(df, color_col):
+    """Pure: returns Plotly trace dict"""
+    ...
+```
+
+## Cached Data Loaders
+Use `@st.cache_data` for expensive data loading:
+```python
+@st.cache_data
+def load_svd_vectors(window: str) -> pd.DataFrame:
+    return db.get_svd_vectors(window)
+```
+
+## Dataclass Config
+```python
+@dataclass
+class Config:
+    db_path: str = "data/stemwijzer.duckdb"
+    default_window: str = "2023"
+    party_colours: dict = field(default_factory=lambda: PARTY_COLOURS)
+```
+
+---
+
+# Imports
+
+## Ordering (convention)
+1. Standard library
+2. Third-party (streamlit, ibis, plotly, sklearn, umap)
+3. Local/relative imports
+
+## Avoid
+- Wildcard imports (`from module import *`)
+- Circular imports (ensure dependency direction: helpers → database → config)

.mindmodel/dependencies/dependencies.yaml

@@ -0,0 +1,78 @@
+# Dependencies
+
+## Core Library Wiring
+
+### Database Layer
+```
+ibis → DuckDB → MotionDatabase singleton (database.py)
+         ↑
+    sqlglot (ibis dependency)
+```
+
+### Data Processing
+```
+pandas → (used throughout for DataFrame operations)
+numpy → (used by sklearn, scipy, umap)
+scipy → spatial.procrustes for window alignment
+```
+
+### ML Pipeline
+```
+sklearn.cluster → KMeans, Procrustes
+sklearn.preprocessing → StandardScaler
+umap → UMAP (optional, graceful fallback)
+```
+
+### Visualization
+```
+plotly → explorer_helpers.py chart builders
+st.plotly_chart → explorer.py rendering
+```
+
+### Streamlit
+```
+streamlit → all pages, @st.cache_data decorators
+```
+
+## Optional Dependencies
+| Package | Required | Fallback |
+|---------|----------|----------|
+| `umap` | No | Use raw SVD vectors (first 2 dims) |
+| `plotly` | Yes | Raises ImportError |
+| `duckdb` | Yes | — |
+| `ibis` | Yes | — |
+| `sklearn` | Yes | — |
+
+## Singleton Instances
+| Module | Instance | Type |
+|--------|----------|------|
+| `database.py` | `db` | `MotionDatabase` |
+| `config.py` | `config` | `Config` (dataclass) |
+| `config.py` | `PARTY_COLOURS` | `dict[str, str]` |
+
+## Key Imports by File
+```
+explorer.py:
+  - import streamlit as st
+  - from database import db
+  - from explorer_helpers import *
+
+explorer_helpers.py:
+  - import pandas as pd
+  - import plotly.graph_objects as go
+  - from database import db (optional, for type hints)
+
+database.py:
+  - import ibis
+  - import duckdb
+  - from config import config, PARTY_COLOURS
+
+config.py:
+  - from dataclasses import dataclass, field
+  - import streamlit as st (optional, for warnings)
+```
+
+## Environment
+- Python ≥3.13
+- Environment variables via `.env` (DB path, API keys)
+- No `.env` values in constraint files (security)

.mindmodel/domain/domain-glossary.yaml

@@ -0,0 +1,107 @@
+# Domain Glossary - Dutch Political Terms
+
+## Core Entities
+
+### Motion / Motie
+- Parliamentary motion submitted by MPs
+- Fields: `id`, `title`, `date`, `category`
+- MPs vote: **For** (+1), **Against** (-1), **Abstain** (0), **Absent**
+
+### MP / Kamerlid
+- Member of Parliament (Tweede Kamerlid)
+- Identified by full name (e.g., "Van Dijk, I.")
+- Has voting record, party affiliation, SVD position vector
+- Historical: `mp_party_history` tracks party changes over time
+
+### Party / Fractie
+- Political party (e.g., "GroenLinks-PvdA", "PVV", "VVD")
+- Party centroids: average SVD position of all MPs in party
+- Aliases: multiple spelling variants exist (see anti-patterns.yaml)
+
+### Vote / Stemming
+- Individual MP's vote on a motion: +1, 0, -1
+- Aggregated to compute SVD vectors
+
+---
+
+## Time & Analysis Concepts
+
+### Window / Tijdsvenster
+- Time period for analysis (annual or quarterly)
+- Values: "2023", "2023-Q1", "2024", etc.
+- SVD vectors computed per window
+- Windows can be aligned across time using Procrustes
+
+### Trajectory
+- MP's position change across multiple windows
+- Computed from `svd_vectors` + window ordering
+- Used for trend analysis in Evolution tab
+
+---
+
+## Mathematical / Algorithmic Terms
+
+### SVD Vector
+- 2D vector from Singular Value Decomposition of MP × Motion vote matrix
+- Represents MP's position in political space
+- `entity_id` in `svd_vectors`: either MP name (when individual MPs) or party name (when party-level)
+
+### Political Compass
+- 2D visualization: X-axis = Left↔Right, Y-axis = Progressive↔Conservative
+- SVD vectors mapped to compass quadrants
+- UMAP used for projection
+
+### Procrustes Alignment
+- Algorithm to align SVD vectors across time windows
+- Ensures comparable positions across years/quarters
+- Implemented via `scipy.spatial.procrustes` or scikit-learn
+
+### Centroid
+- Geometric center of a set of points
+- Party centroid = average SVD position of all MPs in that party
+- Computed from `svd_vectors` filtered by party
+
+### UMAP
+- Uniform Manifold Approximation and Projection
+- Dimensionality reduction for visualization
+- Optional dependency — graceful fallback if unavailable
+
+---
+
+## Visualization
+
+### PARTY_COLOURS
+- Dict mapping party names to hex color codes
+- Used in all Plotly charts for consistent party coloring
+- Source: `config.py` → `PARTY_COLOURS` constant
+- **Issue**: 3 separate alias dictionaries exist (no single source of truth)
+
+---
+
+## Application Pages
+
+### Home
+- Landing page with app overview
+
+### Stemwijzer (Quiz)
+- User answers questions → matched to parties
+- Thin wrapper around quiz module
+
+### Explorer (4 tabs)
+- **Motion tab**: SVD positions colored by vote on selected motion
+- **MP tab**: Individual MP trajectories across windows
+- **Party tab**: Party centroids with members as scatter
+- **Evolution tab**: How positions change over time
+
+---
+
+## Database Table Reference
+| Table | Key Fields |
+|-------|-----------|
+| `motions` | id, title, date, category |
+| `mp_votes` | mp_id, motion_id, vote |
+| `svd_vectors` | entity_id, window, vector_2d (list[2]) |
+| `party_centroids` | party, window, centroid_2d |
+| `mp_party_history` | mp_id, party, start_date, end_date |
+| `windows` | window_id, start_date, end_date, period_type |
+| `mp_trajectories` | mp_id, window, trajectory_vector |

.mindmodel/examples/api-client-example.py

@@ -0,0 +1,196 @@
+"""Example: TweedeKamerAPI usage - from api_client.py and actual codebase."""
+
+from datetime import datetime, timedelta
+from typing import Dict, List
+
+# Import the API client
+from api_client import TweedeKamerAPI
+
+
+# =============================================================================
+# Example 1: Basic API usage
+# =============================================================================
+
+
+def example_fetch_motions():
+    """Fetch recent parliamentary motions from TweedeKamer API."""
+
+    api = TweedeKamerAPI()
+
+    # Fetch motions from last 30 days
+    start_date = datetime.now() - timedelta(days=30)
+
+    try:
+        motions = api.get_motions(start_date=start_date, limit=100)
+
+        print(f"Fetched {len(motions)} motions")
+
+        for motion in motions[:5]:  # Show first 5
+            print(f"  - {motion.get('title', 'N/A')}")
+
+        return motions
+    finally:
+        api.close()
+
+
+# =============================================================================
+# Example 2: Fetching with date range
+# =============================================================================
+
+
+def example_date_range():
+    """Fetch motions from a specific date range."""
+
+    api = TweedeKamerAPI()
+
+    start = datetime(2024, 1, 1)
+    end = datetime(2024, 3, 31)  # Q1 2024
+
+    try:
+        motions = api.get_motions(start_date=start, end_date=end, limit=500)
+
+        # Group by policy area
+        by_area = {}
+        for m in motions:
+            area = m.get("policy_area", "Onbekend")
+            by_area.setdefault(area, []).append(m)
+
+        for area, area_motions in sorted(by_area.items()):
+            print(f"{area}: {len(area_motions)} motions")
+
+        return motions
+    finally:
+        api.close()
+
+
+# =============================================================================
+# Example 3: Context manager usage
+# =============================================================================
+
+
+def example_context_manager():
+    """Use API client as context manager."""
+
+    with TweedeKamerAPI() as api:
+        motions = api.get_motions(
+            start_date=datetime.now() - timedelta(days=7), limit=50
+        )
+
+        print(f"Fetched {len(motions)} motions this week")
+
+        return motions
+
+
+# =============================================================================
+# Example 4: Processing voting records
+# =============================================================================
+
+
+def example_process_votes():
+    """Process individual voting records from API."""
+
+    api = TweedeKamerAPI()
+
+    start_date = datetime.now() - timedelta(days=7)
+
+    try:
+        # Get voting records directly
+        voting_records, besluit_meta = api._get_voting_records(
+            start_date=start_date, limit=1000
+        )
+
+        print(f"Fetched {len(voting_records)} voting records")
+        print(f"From {len(besluit_meta)} unique decisions")
+
+        # Count votes by party
+        party_votes = {}
+        for record in voting_records:
+            party = record.get("Fractie", "Onbekend")
+            vote = record.get("Soort", "Onbekend")
+            party_votes.setdefault(party, {})[vote] = (
+                party_votes.get(party, {}).get(vote, 0) + 1
+            )
+
+        for party, votes in sorted(party_votes.items()):
+            total = sum(votes.values())
+            voor = votes.get("Voor", 0)
+            print(f"{party}: {total} votes ({voor} voor)")
+
+        return voting_records
+    finally:
+        api.close()
+
+
+# =============================================================================
+# Example 5: Safe API call with fallback
+# =============================================================================
+
+
+def example_safe_call():
+    """Make API call with safe fallback on failure."""
+
+    api = TweedeKamerAPI()
+
+    try:
+        # This will return [] on any error
+        motions = api.get_motions(
+            start_date=datetime.now() - timedelta(days=30), limit=100
+        )
+
+        if not motions:
+            print("No motions returned - using cached data")
+            # Fallback to cached/local data
+            from database import db
+
+            return db.get_filtered_motions(limit=10)
+
+        return motions
+    finally:
+        api.close()
+
+
+# =============================================================================
+# Example 6: Pagination handling
+# =============================================================================
+
+
+def example_pagination():
+    """Understand how pagination works in the API."""
+
+    api = TweedeKamerAPI()
+
+    start_date = datetime.now() - timedelta(days=365)
+
+    # Simulate pagination
+    page_size = 250
+    total_limit = 500
+
+    all_motions = []
+    skip = 0
+
+    while len(all_motions) < total_limit:
+        print(f"Fetching page with skip={skip}...")
+
+        # In real usage, get_motions handles pagination internally
+        # This demonstrates what's happening under the hood
+        page_motions = api._fetch_page(start_date=start_date, skip=skip, top=page_size)
+
+        if not page_motions:
+            break
+
+        all_motions.extend(page_motions)
+        skip += page_size
+
+        if len(page_motions) < page_size:
+            break  # Last page
+
+    print(f"Total fetched: {len(all_motions)} motions")
+    return all_motions
+
+
+if __name__ == "__main__":
+    print("=== Basic Fetch ===")
+    example_fetch_motions()
+
+    print("\n=== Process Votes ===")
+    example_process_votes()

.mindmodel/examples/database-example.py

@@ -0,0 +1,191 @@
+"""Example: MotionDatabase usage - from database.py and actual codebase."""
+
+from typing import Dict, List, Optional
+import duckdb
+import json
+from config import config
+
+# Import the singleton instance
+from database import db
+
+
+# =============================================================================
+# Example 1: Getting filtered motions
+# =============================================================================
+
+
+def example_get_filtered_motions():
+    """Get controversial motions from a specific policy area."""
+
+    motions = db.get_filtered_motions(
+        policy_area="Klimaat",
+        min_margin=0.0,
+        max_margin=0.3,  # Controversial: close margin
+        limit=10,
+    )
+
+    for motion in motions:
+        print(f"{motion['title']}: {motion['winning_margin']:.1%} margin")
+
+    return motions
+
+
+# =============================================================================
+# Example 2: Creating a voting session
+# =============================================================================
+
+
+def example_voting_session():
+    """Create a new user session and record votes."""
+
+    # Create session for 10 motions
+    session_id = db.create_session(total_motions=10)
+    print(f"Created session: {session_id}")
+
+    # Get motions for the session
+    motions = db.get_filtered_motions(policy_area="Alle", limit=10)
+
+    # Record votes
+    for motion in motions:
+        # In real app, user would choose vote
+        vote = "Voor"  # Example vote
+        db.record_vote(session_id=session_id, motion_id=motion["id"], vote=vote)
+
+    # Get results
+    results = db.get_party_results(session_id)
+
+    for party, result in sorted(results.items(), key=lambda x: -x[1]["agreement"]):
+        print(f"{party}: {result['agreement']:.1%} agreement")
+
+    return results
+
+
+# =============================================================================
+# Example 3: Working with DuckDB connections directly
+# =============================================================================
+
+
+def example_direct_duckdb():
+    """Example of proper DuckDB connection handling."""
+
+    conn = duckdb.connect(config.DATABASE_PATH)
+    try:
+        # Get motion with votes
+        result = conn.execute(
+            """
+            SELECT m.*, 
+                   JSON_EXTRACT(voting_results, '$.total_votes') as total_votes
+            FROM motions m
+            WHERE m.id = ?
+        """,
+            (123,),
+        ).fetchone()
+
+        if result:
+            print(f"Motion: {result[1]}")  # title is index 1
+
+        return result
+    finally:
+        conn.close()
+
+
+# =============================================================================
+# Example 4: Bulk operations
+# =============================================================================
+
+
+def example_bulk_insert():
+    """Example of bulk inserting motions."""
+
+    # Sample data
+    motions = [
+        {
+            "title": "Motion about climate policy",
+            "description": "Proposal to reduce emissions",
+            "date": "2024-01-15",
+            "policy_area": "Klimaat",
+            "voting_results": json.dumps({"Voor": 75, "Tegen": 65}),
+            "winning_margin": 0.07,
+            "controversy_score": 0.85,
+        },
+        {
+            "title": "Motion about healthcare",
+            "description": "Increase healthcare budget",
+            "date": "2024-01-20",
+            "policy_area": "Zorg",
+            "voting_results": json.dumps({"Voor": 90, "Tegen": 50}),
+            "winning_margin": 0.29,
+            "controversy_score": 0.42,
+        },
+    ]
+
+    conn = duckdb.connect(config.DATABASE_PATH)
+    try:
+        for motion in motions:
+            conn.execute(
+                """
+                INSERT INTO motions 
+                (title, description, date, policy_area, voting_results, 
+                 winning_margin, controversy_score)
+                VALUES (?, ?, ?, ?, ?, ?, ?)
+            """,
+                (
+                    motion["title"],
+                    motion["description"],
+                    motion["date"],
+                    motion["policy_area"],
+                    motion["voting_results"],
+                    motion["winning_margin"],
+                    motion["controversy_score"],
+                ),
+            )
+        conn.close()
+        print(f"Inserted {len(motions)} motions")
+    except Exception as e:
+        conn.close()
+        print(f"Error inserting motions: {e}")
+
+
+# =============================================================================
+# Example 5: Query with aggregation
+# =============================================================================
+
+
+def example_aggregation():
+    """Example of aggregate queries."""
+
+    conn = duckdb.connect(config.DATABASE_PATH)
+    try:
+        # Get statistics by policy area
+        results = conn.execute("""
+            SELECT 
+                policy_area,
+                COUNT(*) as motion_count,
+                AVG(winning_margin) as avg_margin,
+                AVG(controversy_score) as avg_controversy
+            FROM motions
+            WHERE policy_area IS NOT NULL
+            GROUP BY policy_area
+            ORDER BY motion_count DESC
+        """).fetchall()
+
+        for row in results:
+            print(
+                f"{row[0]}: {row[1]} motions, "
+                f"avg margin {row[2]:.1%}, "
+                f"controversy {row[3]:.2f}"
+            )
+
+        conn.close()
+        return results
+    except Exception as e:
+        conn.close()
+        return []
+
+
+if __name__ == "__main__":
+    print("=== Filtered Motions ===")
+    example_get_filtered_motions()
+
+    print("\n=== Aggregation ===")
+    example_aggregation()

.mindmodel/examples/pipeline-example.py

@@ -0,0 +1,217 @@
+"""Example: Pipeline phase execution - from pipeline/run_pipeline.py and actual codebase."""
+
+import argparse
+from datetime import date, timedelta
+from typing import List, Tuple
+
+# Import pipeline modules
+from pipeline.fetch_mp_metadata import fetch_mp_metadata
+from pipeline.extract_mp_votes import extract_mp_votes
+from pipeline.svd_pipeline import run_svd_pipeline
+from pipeline.text_pipeline import run_text_pipeline
+from pipeline.fusion import run_fusion
+
+from database import MotionDatabase
+
+
+# =============================================================================
+# Example 1: Running full pipeline
+# =============================================================================
+
+
+def example_full_pipeline():
+    """Run the complete data ingestion pipeline."""
+
+    # Parse arguments like CLI would
+    parser = argparse.ArgumentParser(description="Pipeline runner")
+    parser.add_argument("--db-path", default="data/motions.db")
+    parser.add_argument("--start-date", default=None)
+    parser.add_argument("--end-date", default=None)
+    parser.add_argument(
+        "--window-size", choices=["quarterly", "annual"], default="quarterly"
+    )
+    parser.add_argument("--svd-k", type=int, default=50)
+
+    args = parser.parse_args([])
+
+    # Resolve dates
+    end_date = date.fromisoformat(args.end_date) if args.end_date else date.today()
+    start_date = (
+        date.fromisoformat(args.start_date)
+        if args.start_date
+        else end_date - timedelta(days=730)
+    )
+
+    print(f"Running pipeline: {start_date} → {end_date}")
+    print(f"Window size: {args.window_size}")
+    print(f"DB path: {args.db_path}")
+
+    # Initialize database
+    db = MotionDatabase(args.db_path)
+
+    # Phase 1: Fetch MP metadata
+    print("\n=== Phase 1: MP Metadata ===")
+    n_mp = fetch_mp_metadata(db_path=args.db_path)
+    print(f"Processed {n_mp} MPs")
+
+    # Phase 2: Extract MP votes
+    print("\n=== Phase 2: Extract Votes ===")
+    n_votes = extract_mp_votes(db_path=args.db_path)
+    print(f"Extracted {n_votes} vote records")
+
+    # Phase 3: Generate time windows
+    print("\n=== Phase 3: SVD Pipeline ===")
+    windows = generate_windows(start_date, end_date, args.window_size)
+    print(f"Generated {len(windows)} windows: {windows}")
+
+    # Phase 4: SVD per window
+    run_svd_pipeline(db, windows, args.svd_k)
+    print(f"Computed SVD for {len(windows)} windows")
+
+    # Phase 5: Text embeddings
+    print("\n=== Phase 4: Text Embeddings ===")
+    run_text_pipeline(args.db_path, batch_size=50)
+    print("Text embeddings completed")
+
+    # Phase 6: Fusion
+    print("\n=== Phase 5: Fusion ===")
+    run_fusion(args.db_path, windows)
+    print("Fusion completed")
+
+    print("\n=== Pipeline Complete ===")
+
+
+# =============================================================================
+# Example 2: Generate time windows
+# =============================================================================
+
+
+def generate_windows(
+    start: date, end: date, granularity: str
+) -> List[Tuple[str, str, str]]:
+    """Generate time windows for pipeline processing."""
+
+    windows = []
+    cursor = date(start.year, start.month, 1)
+
+    if granularity == "annual":
+        cursor = date(start.year, 1, 1)
+        while cursor <= end:
+            year_end = date(cursor.year, 12, 31)
+            w_end = min(year_end, end)
+            windows.append((str(cursor.year), cursor.isoformat(), w_end.isoformat()))
+            cursor = date(cursor.year + 1, 1, 1)
+    else:
+        # quarterly
+        quarter_starts = {1: 1, 2: 4, 3: 7, 4: 10}
+        quarter_ends = {1: 3, 2: 6, 3: 9, 4: 12}
+
+        q = (cursor.month - 1) // 3 + 1
+        cursor = date(cursor.year, quarter_starts[q], 1)
+
+        while cursor <= end:
+            q = (cursor.month - 1) // 3 + 1
+            import calendar
+
+            q_end_month = quarter_ends[q]
+            last_day = calendar.monthrange(cursor.year, q_end_month)[1]
+            q_end = date(cursor.year, q_end_month, last_day)
+            w_end = min(q_end, end)
+            window_id = f"{cursor.year}-Q{q}"
+            windows.append((window_id, cursor.isoformat(), w_end.isoformat()))
+            cursor = q_end + timedelta(days=1)
+
+    return windows
+
+
+def example_window_generation():
+    """Example of window generation."""
+
+    start = date(2023, 1, 1)
+    end = date(2024, 6, 30)
+
+    print("Quarterly windows:")
+    quarterly = generate_windows(start, end, "quarterly")
+    for wid, s, e in quarterly:
+        print(f"  {wid}: {s} to {e}")
+
+    print("\nAnnual windows:")
+    annual = generate_windows(start, end, "annual")
+    for wid, s, e in annual:
+        print(f"  {wid}: {s} to {e}")
+
+
+# =============================================================================
+# Example 3: Running individual phases
+# =============================================================================
+
+
+def example_individual_phases():
+    """Run pipeline phases individually for debugging."""
+
+    db_path = "data/motions.db"
+    db = MotionDatabase(db_path)
+
+    # Only run MP metadata fetch
+    print("Fetching MP metadata...")
+    n = fetch_mp_metadata(db_path=db_path)
+    print(f"  {n} MPs processed")
+
+    # Only run vote extraction
+    print("Extracting votes...")
+    n = extract_mp_votes(db_path=db_path)
+    print(f"  {n} votes extracted")
+
+    # Only run SVD for specific window
+    print("Computing SVD...")
+    windows = [("2024-Q1", "2024-01-01", "2024-03-31")]
+    run_svd_pipeline(db, windows, k=50)
+    print("  SVD computed")
+
+    # Only run text embeddings
+    print("Computing embeddings...")
+    run_text_pipeline(db_path, batch_size=25)  # Smaller batch for testing
+    print("  Embeddings computed")
+
+
+# =============================================================================
+# Example 4: Dry run
+# =============================================================================
+
+
+def example_dry_run():
+    """Show what pipeline would do without making changes."""
+
+    print("DRY RUN - no writes will be made")
+
+    start_date = date(2024, 1, 1)
+    end_date = date(2024, 6, 30)
+
+    # Generate and show windows
+    windows = generate_windows(start_date, end_date, "quarterly")
+
+    print(f"Would process {len(windows)} windows:")
+    for wid, s, e in windows:
+        print(f"  {wid}: {s} to {e}")
+
+    print("\nWould run phases:")
+    print("  1. fetch_mp_metadata")
+    print("  2. extract_mp_votes")
+    print("  3. svd_pipeline")
+    print("  4. text_pipeline")
+    print("  5. fusion")
+
+
+if __name__ == "__main__":
+    import logging
+
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s %(levelname)s %(name)s: %(message)s",
+    )
+
+    print("=== Window Generation ===")
+    example_window_generation()
+
+    print("\n=== Dry Run ===")
+    example_dry_run()

.mindmodel/examples/streamlit-page-example.py

@@ -0,0 +1,316 @@
+"""Example: Streamlit page patterns - from actual pages/ files."""
+
+import streamlit as st
+
+
+# =============================================================================
+# Example 1: Home page (Home.py)
+# =============================================================================
+
+
+def render_home_page():
+    """Simplified version of Home.py."""
+
+    st.set_page_config(
+        page_title="Motief: de stematlas",
+        page_icon="🗺️",
+        layout="centered",
+        initial_sidebar_state="expanded",
+    )
+
+    st.title("🗺️ Motief: de stematlas")
+    st.markdown(
+        "**Motief** brengt de Nederlandse Tweede Kamer in kaart op basis van "
+        "echte stemmingen over moties. Gebruik de Stemwijzer om te ontdekken welke "
+        "partij het beste bij jouw standpunten past, of verken de politieke ruimte "
+        "zelf in de Explorer."
+    )
+
+    st.divider()
+
+    col1, col2 = st.columns(2)
+
+    with col1:
+        st.subheader("🗳️ Stemwijzer")
+        st.markdown(
+            "Stem op echte Tweede Kamer moties en zie welke partij het "
+            "dichtst bij jouw keuzes staat."
+        )
+        st.page_link("pages/1_Stemwijzer.py", label="Open Stemwijzer", icon="🗳️")
+
+    with col2:
+        st.subheader("🔭 Politiek Explorer")
+        st.markdown(
+            "Verken het politieke kompas, partijtrajecten door de tijd, "
+            "en zoek vergelijkbare moties op in het archief."
+        )
+        st.page_link("pages/2_Explorer.py", label="Open Explorer", icon="🔭")
+
+    st.divider()
+    st.caption("Data: Tweede Kamer API · Embeddings: QWEN (via OpenRouter)")
+
+
+# =============================================================================
+# Example 2: Thin page wrapper (pages/1_Stemwijzer.py)
+# =============================================================================
+
+
+def render_stemwijzer_page():
+    """Pattern: thin page that delegates to module function."""
+
+    st.set_page_config(
+        page_title="Stemwijzer",
+        page_icon="🗳️",
+        layout="centered",
+    )
+
+    # Delegate to main module
+    from explorer import build_mp_quiz_tab
+
+    build_mp_quiz_tab("data/motions.db")
+
+
+# =============================================================================
+# Example 3: Session state initialization
+# =============================================================================
+
+
+def init_session_state():
+    """Pattern: Initialize all session state at start."""
+
+    defaults = {
+        "session_id": None,
+        "current_motion_index": 0,
+        "motions": [],
+        "show_results": False,
+        "user_votes": {},
+    }
+
+    for key, default in defaults.items():
+        if key not in st.session_state:
+            st.session_state[key] = default
+
+
+# =============================================================================
+# Example 4: Sidebar configuration
+# =============================================================================
+
+
+def render_sidebar():
+    """Pattern: Sidebar for configuration."""
+
+    with st.sidebar:
+        st.header("Instellingen")
+
+        motion_count = st.slider(
+            "Aantal moties",
+            min_value=5,
+            max_value=25,
+            value=10,
+            help="Hoeveel moties wilt u beantwoorden?",
+        )
+
+        policy_area = st.selectbox(
+            "Beleidsgebied",
+            [
+                "Alle",
+                "Economie",
+                "Klimaat",
+                "Immigratie",
+                "Zorg",
+                "Onderwijs",
+                "Defensie",
+                "Sociale Zaken",
+                "Algemeen",
+            ],
+        )
+
+        margin_range = st.slider(
+            "Controversiële moties (%)",
+            min_value=0,
+            max_value=100,
+            value=(0, 100),
+            help="Filter op hoe omstreden de moties zijn",
+        )
+
+        st.divider()
+
+        if st.button("Start Nieuwe Sessie", type="primary"):
+            return {
+                "motion_count": motion_count,
+                "policy_area": policy_area,
+                "margin_range": margin_range,
+            }
+
+    return None
+
+
+# =============================================================================
+# Example 5: Motion voting interface
+# =============================================================================
+
+
+def render_motion_vote(motion: dict, index: int, total: int):
+    """Pattern: Display motion and voting buttons."""
+
+    st.subheader(f"Motie {index + 1} van {total}")
+
+    # Motion content
+    st.markdown(f"### {motion['title']}")
+
+    col1, col2 = st.columns([3, 1])
+    with col1:
+        if motion.get("layman_explanation"):
+            st.info(motion["layman_explanation"])
+
+        with st.expander("Meer details"):
+            st.markdown(f"**Datum:** {motion.get('date', 'Onbekend')}")
+            st.markdown(f"**Beleidsgebied:** {motion.get('policy_area', 'Onbekend')}")
+
+            if motion.get("description"):
+                st.markdown(f"**Beschrijving:** {motion['description']}")
+
+    with col2:
+        st.metric(
+            label="Winstmarge",
+            value=f"{motion.get('winning_margin', 0):.0%}",
+            delta="Omstreden" if motion.get("controversy_score", 0) > 0.5 else "Helder",
+        )
+
+    st.divider()
+
+    # Voting buttons
+    col1, col2, col3 = st.columns(3)
+
+    with col1:
+        st.button(
+            "👍 **Voor**",
+            on_click=on_vote,
+            args=(motion["id"], "Voor"),
+            use_container_width=True,
+        )
+
+    with col2:
+        st.button(
+            "👎 **Tegen**",
+            on_click=on_vote,
+            args=(motion["id"], "Tegen"),
+            use_container_width=True,
+        )
+
+    with col3:
+        st.button(
+            "🤔 **Onthouden**",
+            on_click=on_vote,
+            args=(motion["id"], "Onthouden"),
+            use_container_width=True,
+        )
+
+
+def on_vote(motion_id: int, vote: str):
+    """Callback when user votes."""
+
+    # Record vote
+    from database import db
+
+    db.record_vote(
+        session_id=st.session_state.session_id, motion_id=motion_id, vote=vote
+    )
+
+    # Update session state
+    st.session_state.user_votes[motion_id] = vote
+
+    # Move to next or show results
+    if st.session_state.current_motion_index < len(st.session_state.motions) - 1:
+        st.session_state.current_motion_index += 1
+    else:
+        st.session_state.show_results = True
+
+    st.rerun()
+
+
+# =============================================================================
+# Example 6: Results display
+# =============================================================================
+
+
+def render_results():
+    """Pattern: Display voting results."""
+
+    from database import db
+
+    st.header("📊 Uw Resultaten")
+
+    # Get party results
+    results = db.get_party_results(st.session_state.session_id)
+
+    if not results:
+        st.warning("Geen resultaten beschikbaar")
+        return
+
+    # Sort by agreement
+    sorted_results = sorted(
+        results.items(), key=lambda x: x[1].get("agreement_percentage", 0), reverse=True
+    )
+
+    # Display top match
+    if sorted_results:
+        top_party, top_data = sorted_results[0]
+        st.success(
+            f"**Uw beste match:** {top_party} ({top_data.get('agreement_percentage', 0):.0%} overeenstemming)"
+        )
+
+    st.divider()
+
+    # Show all parties
+    for party, data in sorted_results:
+        agreement = data.get("agreement_percentage", 0)
+
+        col1, col2 = st.columns([3, 1])
+        with col1:
+            st.markdown(f"**{party}**")
+            st.progress(agreement, text=f"{agreement:.0%}")
+
+        with col2:
+            st.metric("Overeenstemming", f"{agreement:.0%}")
+
+    # Detailed breakdown
+    with st.expander("Details per motie"):
+        for motion in st.session_state.motions:
+            user_vote = st.session_state.user_votes.get(motion["id"], "?")
+            st.markdown(f"- **{motion['title']}**: U={user_vote}")
+
+
+# =============================================================================
+# Example 7: Tabs layout
+# =============================================================================
+
+
+def render_tabs_example():
+    """Pattern: Use tabs for organizing content."""
+
+    tab1, tab2, tab3 = st.tabs(["Compass", "Trajectories", "Zoeken"])
+
+    with tab1:
+        st.subheader("Politiek Kompas")
+        st.write("Visualiseer partijposities in 2D ruimte")
+        # Add compass chart...
+
+    with tab2:
+        st.subheader("Partij Trajectories")
+        st.write("Bekijk hoe partijen door de tijd bewegen")
+        # Add trajectory chart...
+
+    with tab3:
+        st.subheader("Zoek Moties")
+
+        query = st.text_input("Zoekterm")
+        if query:
+            # Search functionality...
+            st.write(f"Zoeken naar: {query}")
+
+
+if __name__ == "__main__":
+    # Demo rendering
+    init_session_state()
+    st.write("Streamlit page structure example")

.mindmodel/patterns/api.yaml

@@ -0,0 +1,265 @@
+# API Client Patterns
+
+## Base API Client Pattern
+
+Using requests.Session for connection pooling:
+
+```python
+# api_client.py
+import requests
+from typing import Dict, List, Optional
+from config import config
+
+class TweedeKamerAPI:
+    def __init__(self):
+        self.odata_base_url = "https://gegevensmagazijn.tweedekamer.nl/OData/v4/2.0"
+        self.session = requests.Session()
+        self.session.headers.update({
+            "Accept": "application/json",
+            "User-Agent": "Dutch-Political-Compass-Tool/1.0",
+        })
+    
+    def get_motions(
+        self,
+        start_date: datetime = None,
+        end_date: datetime = None,
+        limit: int = 500,
+    ) -> List[Dict]:
+        """Get motions with voting results using OData API."""
+        if not start_date:
+            start_date = datetime.now() - timedelta(days=730)
+        
+        try:
+            voting_records, besluit_meta = self._get_voting_records(
+                start_date, end_date, limit
+            )
+            return self._process_voting_records(voting_records, besluit_meta)
+        except Exception as e:
+            print(f"Error fetching motions from API: {e}")
+            return []
+```
+
+## OData Pagination Pattern
+
+Handle server-side pagination with $skip:
+
+```python
+def _get_voting_records(
+    self, 
+    start_date: datetime, 
+    end_date: datetime = None, 
+    limit: int = 50000
+) -> tuple:
+    """Fetch with automatic pagination."""
+    
+    filter_query = (
+        f"GewijzigdOp ge {start_date.strftime('%Y-%m-%d')}T00:00:00Z"
+        " and StemmingsSoort ne null"
+        " and Verwijderd eq false"
+    )
+    
+    page_size = 250  # API caps $top at 250
+    base_url = f"{self.odata_base_url}/Besluit"
+    base_params = {
+        "$filter": filter_query,
+        "$top": page_size,
+        "$expand": "Stemming",
+        "$orderby": "GewijzigdOp desc",
+    }
+    
+    all_records = []
+    skip = 0
+    
+    while len(all_records) < limit:
+        params = {**base_params, "$skip": skip}
+        response = self.session.get(
+            base_url, 
+            params=params, 
+            timeout=config.API_TIMEOUT
+        )
+        response.raise_for_status()
+        data = response.json()
+        
+        besluit_page = data.get("value", [])
+        if not besluit_page:
+            break
+        
+        # Process page
+        for besluit in besluit_page:
+            all_records.extend(self._extract_votes(besluit))
+        
+        skip += page_size
+    
+    return all_records
+```
+
+## Retry with Backoff Pattern
+
+For transient failures:
+
+```python
+# ai_provider.py
+import time
+import random
+from requests.exceptions import ConnectionError
+
+def _post_with_retries(
+    path: str, 
+    json: dict, 
+    retries: int = 3
+) -> requests.Response:
+    """POST with exponential backoff retry."""
+    
+    backoff = 0.5
+    for attempt in range(1, retries + 1):
+        try:
+            resp = requests.post(url, json=json, headers=headers, timeout=10)
+            
+            # Handle rate limiting
+            if resp.status_code == 429:
+                if attempt == retries:
+                    raise ProviderError("Rate limited")
+                
+                retry_after = resp.headers.get("Retry-After")
+                if retry_after:
+                    time.sleep(int(retry_after))
+                else:
+                    sleep = backoff * (2 ** (attempt - 1))
+                    sleep += random.uniform(0, sleep * 0.1)
+                    time.sleep(sleep)
+                continue
+            
+            # Handle server errors
+            if 500 <= resp.status_code < 600:
+                if attempt == retries:
+                    raise ProviderError(f"Server error: {resp.status_code}")
+                time.sleep(backoff * (2 ** (attempt - 1)))
+                continue
+            
+            return resp
+            
+        except ConnectionError as exc:
+            if attempt == retries:
+                raise ProviderError(f"Connection error: {exc}")
+            time.sleep(backoff * (2 ** (attempt - 1)))
+    
+    raise ProviderError("Failed after retries")
+```
+
+## Batch Processing Pattern
+
+Process items in batches to manage API limits:
+
+```python
+def get_embeddings_with_retry(
+    texts: List[str],
+    batch_size: int = 50,
+    retries: int = 3,
+) -> List[Optional[List[float]]]:
+    """Process embeddings in batches with fallback to single items."""
+    
+    results = [None] * len(texts)
+    
+    i = 0
+    while i < len(texts):
+        end = min(len(texts), i + batch_size)
+        chunk = texts[i:end]
+        
+        # Try batch first
+        try:
+            emb_chunk = get_embeddings_batch(chunk)
+            for j, emb in enumerate(emb_chunk):
+                results[i + j] = emb
+            i = end
+            continue
+        except Exception:
+            pass
+        
+        # Fallback: single items
+        for j, text in enumerate(chunk):
+            try:
+                results[i + j] = get_embedding(text)
+            except Exception:
+                results[i + j] = None
+        
+        i = end
+    
+    return results
+```
+
+## Response Validation Pattern
+
+Validate API responses before processing:
+
+```python
+def _process_response(self, response: requests.Response) -> Dict:
+    """Validate and parse API response."""
+    
+    response.raise_for_status()
+    data = response.json()
+    
+    if "value" not in data:
+        raise ValueError("Unexpected response format: missing 'value' key")
+    
+    return data
+
+def _validate_besluit(self, besluit: Dict) -> bool:
+    """Check required fields exist."""
+    required = ["Id", "GewijzigdOp"]
+    return all(field in besluit for field in required)
+```
+
+## Error Handling Patterns
+
+Always provide safe fallbacks:
+
+```python
+def safe_api_call(self, endpoint: str, params: Dict = None) -> List[Dict]:
+    """Call API with error handling and fallback."""
+    try:
+        response = self.session.get(
+            endpoint, 
+            params=params, 
+            timeout=config.API_TIMEOUT
+        )
+        response.raise_for_status()
+        data = response.json()
+        return data.get("value", [])
+    except requests.Timeout:
+        _logger.warning(f"API timeout for {endpoint}")
+        return []
+    except requests.HTTPError as e:
+        _logger.error(f"HTTP error: {e}")
+        return []
+    except Exception as e:
+        _logger.error(f"API call failed: {e}")
+        return []
+```
+
+## Session Management
+
+Reuse session for connection pooling:
+
+```python
+class TweedeKamerAPI:
+    def __init__(self):
+        self.session = requests.Session()
+        self.session.headers.update({
+            "Accept": "application/json",
+            "User-Agent": "Dutch-Political-Compass-Tool/1.0",
+        })
+    
+    def close(self):
+        """Clean up session when done."""
+        self.session.close()
+    
+    def __enter__(self):
+        return self
+    
+    def __exit__(self, *args):
+        self.close()
+
+# Usage
+with TweedeKamerAPI() as api:
+    motions = api.get_motions(start_date)
+```

.mindmodel/patterns/architecture.yaml

@@ -0,0 +1,230 @@
+# Architectural Patterns
+
+## Repository Pattern
+
+The `MotionDatabase` class acts as a repository, encapsulating all database operations behind a clean interface.
+
+```python
+# database.py
+class MotionDatabase:
+    def __init__(self, db_path: str = config.DATABASE_PATH):
+        self.db_path = db_path
+        self._init_database()
+    
+    def get_motion(self, motion_id: int) -> Optional[Dict]:
+        """Get a single motion by ID."""
+        conn = duckdb.connect(self.db_path)
+        try:
+            result = conn.execute(
+                "SELECT * FROM motions WHERE id = ?", (motion_id,)
+            ).fetchone()
+            return result
+        finally:
+            conn.close()
+    
+    def get_filtered_motions(
+        self,
+        policy_area: str = "Alle",
+        min_margin: float = 0.0,
+        max_margin: float = 1.0,
+        limit: int = 10
+    ) -> List[Dict]:
+        """Get filtered list of motions."""
+        ...
+```
+
+**Usage**: Import the singleton instance for all DB operations.
+```python
+from database import db
+
+motions = db.get_filtered_motions(policy_area="Klimaat", limit=20)
+```
+
+## Facade Pattern
+
+Simplified interfaces over complex subsystems.
+
+### MotionDatabase Facade
+```python
+# Single entry point for all database operations
+db = MotionDatabase()  # Singleton instance
+
+# Operations are abstracted:
+db.create_session(total_motions)
+db.record_vote(session_id, motion_id, vote)
+db.get_party_results(session_id)
+```
+
+### API Client Facade
+```python
+# api_client.py
+class TweedeKamerAPI:
+    def __init__(self):
+        self.session = requests.Session()  # Connection pooling
+    
+    def get_motions(self, start_date, end_date) -> List[Dict]:
+        """Simple interface hiding OData pagination details."""
+        voting_records, besluit_meta = self._get_voting_records(start_date, end_date)
+        return self._process_voting_records(voting_records, besluit_meta)
+```
+
+### MotionScraper Facade
+```python
+# scraper.py (if used)
+class MotionScraper:
+    def get_motion_content(self, url: str) -> Optional[str]:
+        """Extract body text from official website."""
+        ...
+```
+
+## Pipeline Pattern
+
+Sequential phases with explicit dependencies:
+
+```
+pipeline/run_pipeline.py
+├── Phase 1: fetch_mp_metadata
+│   └── pipeline/fetch_mp_metadata.py
+├── Phase 2: extract_mp_votes
+│   └── pipeline/extract_mp_votes.py
+├── Phase 3: svd_pipeline
+│   └── pipeline/svd_pipeline.py
+├── Phase 4: text_pipeline (gap-fill)
+│   └── pipeline/text_pipeline.py
+└── Phase 5: fusion (combine SVD + text)
+    └── pipeline/fusion.py
+```
+
+### Phase Orchestration
+```python
+# pipeline/run_pipeline.py
+def run(args: argparse.Namespace) -> int:
+    db = MotionDatabase(args.db_path)
+    
+    # Phase 1: MP metadata
+    if not args.skip_metadata:
+        from pipeline.fetch_mp_metadata import fetch_mp_metadata
+        fetch_mp_metadata(db_path=db.db_path)
+    
+    # Phase 2: Extract votes
+    if not args.skip_extract:
+        from pipeline.extract_mp_votes import extract_mp_votes
+        extract_mp_votes(db_path=db.db_path)
+    
+    # Phase 3: SVD per window
+    if not args.skip_svd:
+        from pipeline.svd_pipeline import run_svd_pipeline
+        run_svd_pipeline(db, windows, args.svd_k)
+    
+    # ... additional phases
+```
+
+## Strategy Pattern
+
+Interchangeable algorithms for axis computation:
+
+```python
+# analysis/political_axis.py
+def compute_political_axis(
+    vectors: Dict[str, np.ndarray],
+    method: str = "pca"  # or "anchor"
+) -> Tuple[np.ndarray, np.ndarray]:
+    """Compute political axis using specified method.
+    
+    Methods:
+    - 'pca': Use first principal component
+    - 'anchor': Use predefined anchor motions
+    """
+    if method == "pca":
+        return _compute_pca_axis(vectors)
+    elif method == "anchor":
+        return _compute_anchor_axis(vectors)
+```
+
+## Visitor Pattern
+
+External operations on data structures:
+
+```python
+# analysis/trajectory.py
+def _procrustes_align_windows(
+    window_vecs: Dict[str, Dict[str, np.ndarray]],
+    min_overlap: int = 5,
+) -> Dict[str, Dict[str, np.ndarray]]:
+    """Align SVD vectors across windows using Procrustes rotations.
+    
+    Takes the first window as reference and aligns each subsequent window
+    to it via orthogonal Procrustes on the set of common entities.
+    """
+```
+
+## Builder Pattern
+
+Configuration via method chaining:
+
+```python
+# CLI argument parsing
+parser = argparse.ArgumentParser(description="Pipeline runner")
+parser.add_argument("--db-path", default="data/motions.db")
+parser.add_argument("--start-date", default=None)
+parser.add_argument("--end-date", default=None)
+parser.add_argument("--window-size", choices=["quarterly", "annual"], default="quarterly")
+parser.add_argument("--svd-k", type=int, default=50)
+```
+
+## Decorator Pattern
+
+Retry logic for transient failures:
+
+```python
+# pipeline/ai_provider_wrapper.py
+def get_embeddings_with_retry(
+    texts: List[str],
+    retries: int = 3,
+    batch_size: int = 50,
+) -> List[Optional[List[float]]]:
+    """Return embeddings with automatic retry on failure."""
+    for attempt in range(1, retries + 1):
+        try:
+            return _embedder(texts, batch_size=len(texts))
+        except Exception as exc:
+            if attempt == retries:
+                break
+            time.sleep(backoff * (2 ** (attempt - 1)))
+    return [None] * len(texts)  # Safe fallback
+```
+
+## Data Patterns
+
+### Batch Processing
+Process items in chunks to manage memory and API limits:
+```python
+for i in range(0, len(items), batch_size):
+    chunk = items[i:i + batch_size]
+    process_batch(chunk)
+```
+
+### Caching
+Pre-compute and store expensive results:
+```python
+# SimilarityCache table stores computed similarities
+db.get_similarity(motion_a, motion_b)
+```
+
+### Lazy Loading
+Load data only when needed:
+```python
+class MotionDatabase:
+    @property
+    def _connection(self):
+        if self._conn is None:
+            self._conn = duckdb.connect(self.db_path)
+        return self._conn
+```
+
+### Vectorization
+Use numpy for batch operations:
+```python
+vectors = np.array([v for v in entity_vectors.values()])
+normalized = vectors / np.linalg.norm(vectors, axis=1, keepdims=True)
+```

.mindmodel/patterns/database.yaml

@@ -0,0 +1,239 @@
+# DuckDB Database Patterns
+
+## Connection Management
+
+### Pattern 1: Short-lived per Method (Most Common)
+
+Always create a new connection, use try/finally for cleanup:
+
+```python
+# database.py
+class MotionDatabase:
+    def get_motion(self, motion_id: int) -> Optional[Dict]:
+        conn = duckdb.connect(self.db_path)
+        try:
+            result = conn.execute(
+                "SELECT * FROM motions WHERE id = ?", 
+                (motion_id,)
+            ).fetchone()
+            conn.close()
+            return result
+        except Exception:
+            conn.close()
+            return None
+    
+    def get_filtered_motions(
+        self, 
+        policy_area: str = "Alle",
+        min_margin: float = 0.0,
+        max_margin: float = 1.0,
+        limit: int = 10
+    ) -> List[Dict]:
+        conn = duckdb.connect(self.db_path)
+        try:
+            query = """
+                SELECT * FROM motions 
+                WHERE (? = 'Alle' OR policy_area = ?)
+                AND winning_margin BETWEEN ? AND ?
+                ORDER BY RANDOM()
+                LIMIT ?
+            """
+            rows = conn.execute(query, (policy_area, policy_area, min_margin, max_margin, limit)).fetchall()
+            conn.close()
+            return rows
+        except Exception:
+            conn.close()
+            return []
+```
+
+### Pattern 2: With Statement (Cleaner)
+
+```python
+def execute_query(self, query: str, params: tuple = ()):
+    with duckdb.connect(self.db_path) as conn:
+        return conn.execute(query, params).fetchall()
+```
+
+### Pattern 3: Lazy Connection Caching
+
+For frequently accessed connections:
+
+```python
+class MotionDatabase:
+    def __init__(self, db_path: str = config.DATABASE_PATH):
+        self.db_path = db_path
+        self._conn = None
+    
+    @property
+    def connection(self):
+        if self._conn is None:
+            self._conn = duckdb.connect(self.db_path)
+        return self._conn
+    
+    def close(self):
+        if self._conn:
+            self._conn.close()
+            self._conn = None
+```
+
+## Table Initialization
+
+Create tables with proper constraints and sequences:
+
+```python
+def _init_database(self):
+    conn = duckdb.connect(self.db_path)
+    
+    # Create sequence for auto-incrementing IDs
+    try:
+        conn.execute("CREATE SEQUENCE IF NOT EXISTS motions_id_seq START 1")
+    except:
+        pass
+    
+    # Create tables
+    conn.execute("""
+        CREATE TABLE IF NOT EXISTS motions (
+            id INTEGER DEFAULT nextval('motions_id_seq'),
+            title TEXT NOT NULL,
+            description TEXT,
+            date DATE,
+            policy_area TEXT,
+            voting_results JSON,
+            winning_margin FLOAT,
+            controversy_score FLOAT,
+            layman_explanation TEXT,
+            externe_identifier TEXT,
+            body_text TEXT,
+            url TEXT UNIQUE,
+            created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+            PRIMARY KEY (id)
+        )
+    """)
+    
+    # Add columns to existing tables safely
+    try:
+        conn.execute("ALTER TABLE motions ADD COLUMN IF NOT EXISTS body_text TEXT")
+    except Exception:
+        pass  # Column may already exist
+    
+    conn.close()
+```
+
+## JSON Column Handling
+
+Store and retrieve JSON data:
+
+```python
+# Insert JSON
+def store_motion(self, motion: Dict):
+    conn = duckdb.connect(self.db_path)
+    try:
+        conn.execute(
+            "INSERT INTO motions (title, voting_results) VALUES (?, ?)",
+            (motion["title"], json.dumps(motion["voting_results"]))
+        )
+        conn.close()
+    except Exception:
+        conn.close()
+
+# Query JSON
+def get_motions_with_votes(self, party: str) -> List[Dict]:
+    conn = duckdb.connect(self.db_path)
+    try:
+        rows = conn.execute("""
+            SELECT title, voting_results 
+            FROM motions 
+            WHERE JSON_EXTRACT(voting_results, '$.party') = ?
+        """, (party,)).fetchall()
+        conn.close()
+        return rows
+    except Exception:
+        conn.close()
+        return []
+```
+
+## Query Patterns
+
+### Parameterized Queries (Always!)
+```python
+# SAFE - uses parameterized query
+conn.execute("SELECT * FROM motions WHERE id = ?", (motion_id,))
+
+# AVOID - SQL injection risk
+# conn.execute(f"SELECT * FROM motions WHERE id = {motion_id}")  # BAD!
+```
+
+### Batch Inserts
+```python
+def bulk_insert_motions(self, motions: List[Dict]):
+    conn = duckdb.connect(self.db_path)
+    try:
+        for motion in motions:
+            conn.execute(
+                """INSERT OR IGNORE INTO motions 
+                   (title, date, policy_area) VALUES (?, ?, ?)""",
+                (motion["title"], motion["date"], motion["policy_area"])
+            )
+        conn.close()
+    except Exception:
+        conn.close()
+```
+
+### Aggregation Queries
+```python
+def get_party_vote_stats(self, party: str) -> Dict:
+    conn = duckdb.connect(self.db_path)
+    try:
+        result = conn.execute("""
+            SELECT 
+                COUNT(*) as total_votes,
+                SUM(CASE WHEN vote = 'Voor' THEN 1 ELSE 0 END) as voor,
+                SUM(CASE WHEN vote = 'Tegen' THEN 1 ELSE 0 END) as tegen
+            FROM mp_votes
+            WHERE party = ?
+        """, (party,)).fetchone()
+        conn.close()
+        return {"total": result[0], "voor": result[1], "tegen": result[2]}
+    except Exception:
+        conn.close()
+        return {"total": 0, "voor": 0, "tegen": 0}
+```
+
+## Error Handling
+
+Always close connections in finally block or with context manager:
+
+```python
+def safe_query(self, query: str, params: tuple = ()):
+    conn = None
+    try:
+        conn = duckdb.connect(self.db_path)
+        result = conn.execute(query, params).fetchall()
+        return result
+    except Exception as e:
+        _logger.error(f"Query failed: {e}")
+        return []
+    finally:
+        if conn:
+            conn.close()
+```
+
+## Testing with Mock
+
+For unit tests without DuckDB:
+
+```python
+# In MotionDatabase.__init__
+def __init__(self, db_path: str = config.DATABASE_PATH):
+    self.db_path = db_path
+    self._file_mode = duckdb is None
+    
+    if duckdb is None:
+        # Create JSON fallback files
+        for p in (f"{db_path}.embeddings.json", f"{db_path}.similarity_cache.json"):
+            if not os.path.exists(p):
+                with open(p, "w") as fh:
+                    fh.write("[]")
+    else:
+        self._init_database()
+```

.mindmodel/patterns/patterns.yaml

@@ -0,0 +1,228 @@
+# Code Patterns
+
+## 1. Page Wrapper Pattern
+Thin Streamlit page files delegate to core modules. Pages contain only route logic, not business logic.
+
+**Example** (pages/1_🗳️_Stemwijzer.py):
+```python
+import streamlit as st
+from quiz_module import render_quiz_page
+
+st.set_page_config(...)
+render_quiz_page()
+```
+
+**Example** (pages/2_🔍_Explorer.py):
+```python
+import streamlit as st
+from explorer import render_explorer
+
+st.set_page_config(...)
+render_explorer()
+```
+
+**Rule**: Pages should have <20 lines of logic. All complexity lives in modules.
+
+---
+
+## 2. Pipeline Pattern
+Data flows: fetch → transform → store
+
+**Location**: `pipeline/` directory
+
+**Pattern**:
+```python
+def run_pipeline():
+    raw_data = fetch_from_source()
+    transformed = transform(raw_data)
+    store(transformed)
+
+def fetch_from_source():
+    # API call or DB query
+    ...
+
+def transform(raw):
+    # Clean, normalize, compute derived fields
+    ...
+```
+
+**Usage**: SVD computation pipeline, data ingestion, motion processing
+
+---
+
+## 3. API Client Pattern
+HTTP client with retry/backoff for external data sources.
+
+**Pattern**:
+```python
+import time
+import requests
+
+def fetch_with_retry(url, max_retries=3):
+    for attempt in range(max_retries):
+        try:
+            response = requests.get(url)
+            response.raise_for_status()
+            return response.json()
+        except requests.RequestException:
+            if attempt < max_retries - 1:
+                time.sleep(2 ** attempt)  # exponential backoff
+            else:
+                raise
+```
+
+---
+
+## 4. Pure Helper Functions
+Functions in `explorer_helpers.py` have no side effects, no IO.
+
+**Pattern**:
+```python
+def compute_party_coords(svd_df, party_map, window):
+    """Pure function: same inputs → same outputs, no side effects."""
+    # Filter, compute, return
+    return result_df
+
+def build_scatter_trace(df, color_col, marker_size=8):
+    """Pure: returns Plotly trace dict, no rendering."""
+    trace = go.Scatter(x=df.x, y=df.y, mode='markers', ...)
+    return trace
+```
+
+**Rule**: No `import streamlit` in helper modules. No file I/O. No global state.
+
+---
+
+## 5. Dummy Fallbacks for Optional Dependencies
+Gracefully degrade when optional packages are unavailable.
+
+**Pattern**:
+```python
+try:
+    import umap
+    HAS_UMAP = True
+except ImportError:
+    HAS_UMAP = False
+    # or provide dummy stub
+
+def project_to_2d(vectors):
+    if HAS_UMAP:
+        return umap.UMAP().fit_transform(vectors)
+    else:
+        return vectors[:, :2]  # fallback: just take first 2 dims
+```
+
+**Used for**: UMAP, Plotly (with fallback to altair or text-only)
+
+---
+
+## 6. Cached Data Loaders
+Expensive DB queries wrapped with `@st.cache_data`.
+
+**Pattern**:
+```python
+@st.cache_data
+def load_svd_vectors(window: str) -> pd.DataFrame:
+    return db.query("SELECT * FROM svd_vectors WHERE window = ?", window)
+
+@st.cache_data
+def load_party_centroids(window: str) -> pd.DataFrame:
+    return db.query("SELECT * FROM party_centroids WHERE window = ?", window)
+
+# Clear cache when data updates
+@st.cache_data
+def load_motions(category: str | None = None) -> pd.DataFrame:
+    ...
+```
+
+**Rule**: Use `ttl=3600` for large datasets. Use `show_spinner=False` where appropriate.
+
+---
+
+## 7. Plotly Dual-Layer Charts
+Charts built with two traces: scatter points + text annotations.
+
+**Pattern**:
+```python
+def build_dual_layer_chart(df, x_col, y_col, label_col):
+    # Layer 1: markers
+    scatter = go.Scatter(
+        x=df[x_col], y=df[y_col],
+        mode='markers',
+        marker=dict(size=10, color=df['color']),
+        name='Parties'
+    )
+    # Layer 2: labels (smaller, non-hoverable)
+    labels = go.Scatter(
+        x=df[x_col], y=df[y_col],
+        mode='text',
+        text=df[label_col],
+        textposition='top center',
+        showlegend=False
+    )
+    return [scatter, labels]
+```
+
+**Used in**: Explorer tab charts, party position plots
+
+---
+
+## 8. Singleton Module Instances
+One shared instance per module, created at import time.
+
+**Pattern**:
+```python
+# database.py
+class MotionDatabase:
+    def __init__(self, db_path=None):
+        self.conn = ibis.duckdb.connect(db_path)
+        self._load_schema()
+
+_db = None
+def get_db():
+    global _db
+    if _db is None:
+        _db = MotionDatabase()
+    return _db
+
+# At module bottom:
+db = MotionDatabase()  # singleton instance
+```
+
+**Also used in**: `config.py` exports `config` and `PARTY_COLOURS`
+
+---
+
+## 9. Dataclass Config Pattern
+Configuration centralized in a `@dataclass`.
+
+**Pattern**:
+```python
+from dataclasses import dataclass, field
+
+@dataclass
+class Config:
+    db_path: str = "data/stemwijzer.duckdb"
+    default_window: str = "2023"
+    cache_ttl: int = 3600
+    party_colours: dict = field(default_factory=lambda: PARTY_COLOURS)
+
+    def __post_init__(self):
+        if not Path(self.db_path).exists():
+            raise FileNotFoundError(f"Database not found: {self.db_path}")
+```
+
+---
+
+## 10. Graceful Degradation with try/except
+Core pattern throughout: attempt operation, fall back gracefully.
+
+**Pattern**:
+```python
+def get_political_position(mp_name, window):
+    try:
+        vectors = load_svd_vectors(window)
+        return vectors[vectors['mp_name'] == mp_name]['vector_2d'].iloc[0]
+    except (KeyError, IndexError):
+        return [0.0, 0.0]  # neutral fallback
+```

.mindmodel/patterns/python.yaml

@@ -0,0 +1,196 @@
+# Python-Specific Patterns
+
+## Singleton Pattern
+
+Use module-level instances for shared resources:
+
+```python
+# database.py
+class MotionDatabase:
+    def __init__(self, db_path: str = config.DATABASE_PATH):
+        self.db_path = db_path
+        self._init_database()
+    
+    def _init_database(self):
+        # Initialize tables on first instantiation
+        ...
+
+# Bottom of file - the singleton
+db = MotionDatabase()
+```
+
+**Usage across the codebase:**
+```python
+# In other modules
+from database import db
+
+def some_function():
+    motions = db.get_filtered_motions(limit=10)
+    return motions
+```
+
+Similarly for other singletons:
+```python
+# summarizer.py
+class MotionSummarizer:
+    def __init__(self):
+        pass  # Stateless
+    
+    def generate_layman_explanation(self, title: str, body: str) -> str:
+        ...
+
+summarizer = MotionSummarizer()
+```
+
+## Dataclass Config Pattern
+
+Use dataclass for configuration with environment variable support:
+
+```python
+# config.py
+from dataclasses import dataclass
+from typing import List
+import os
+
+@dataclass
+class Config:
+    # Database settings
+    DATABASE_PATH = "data/motions.db"
+    
+    # API settings
+    TWEEDE_KAMER_ODATA_API = "https://gegevensmagazijn.tweedekamer.nl/OData/v4/2.0"
+    API_TIMEOUT = 30
+    API_BATCH_SIZE = 250
+    
+    # AI settings
+    OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
+    OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
+    QWEN_MODEL = "qwen/qwen-2.5-72b-instruct"
+    
+    # App settings
+    DEFAULT_MOTION_COUNT = 10
+    SESSION_TIMEOUT_DAYS = 30
+    
+    # Policy areas
+    POLICY_AREAS: List[str] = None
+    def __post_init__(self):
+        self.POLICY_AREAS = [
+            "Alle", "Economie", "Klimaat", "Immigratie", 
+            "Zorg", "Onderwijs", "Defensie", "Sociale Zaken", "Algemeen"
+        ]
+
+config = Config()
+```
+
+**Usage:**
+```python
+from config import config
+
+# Access as attributes
+timeout = config.API_TIMEOUT
+areas = config.POLICY_AREAS
+```
+
+## DuckDB Connection Pattern
+
+Short-lived connections with explicit cleanup:
+
+```python
+class MotionDatabase:
+    def get_motion(self, motion_id: int) -> Optional[Dict]:
+        conn = duckdb.connect(self.db_path)
+        try:
+            result = conn.execute(
+                "SELECT * FROM motions WHERE id = ?", 
+                (motion_id,)
+            ).fetchone()
+            return result
+        finally:
+            conn.close()
+    
+    def get_filtered_motions(self, **kwargs) -> List[Dict]:
+        conn = duckdb.connect(self.db_path)
+        try:
+            rows = conn.execute(query, params).fetchall()
+            return rows
+        except Exception:
+            return []  # Safe fallback
+        finally:
+            conn.close()
+```
+
+**Context manager alternative (preferred when applicable):**
+```python
+def some_operation(self):
+    with duckdb.connect(self.db_path) as conn:
+        result = conn.execute("SELECT ...").fetchall()
+    return result
+```
+
+## Try/Except with Fallback Pattern
+
+Always provide safe fallbacks:
+
+```python
+def get_motion_or_default(self, motion_id: int) -> Dict:
+    try:
+        conn = duckdb.connect(self.db_path)
+        result = conn.execute("SELECT * FROM motions WHERE id = ?", (motion_id,)).fetchone()
+        conn.close()
+        return result if result else {}
+    except Exception:
+        return {}
+```
+
+## Optional Import Pattern
+
+Handle optional dependencies gracefully:
+
+```python
+try:
+    import duckdb
+except Exception:  # pragma: no cover
+    duckdb = None
+
+class MotionDatabase:
+    def __init__(self, db_path: str = config.DATABASE_PATH):
+        self._file_mode = duckdb is None
+        ...
+```
+
+## Property Pattern
+
+Lazy initialization of expensive resources:
+
+```python
+class MotionDatabase:
+    def __init__(self, db_path: str = config.DATABASE_PATH):
+        self.db_path = db_path
+        self._session_cache = None
+    
+    @property
+    def session(self):
+        """Lazy-load expensive resources."""
+        if self._session_cache is None:
+            self._session_cache = self._create_session()
+        return self._session_cache
+```
+
+## Type Annotation Patterns
+
+```python
+from typing import Dict, List, Optional, Tuple, Any
+
+# Optional with None default
+def get_motion(self, motion_id: Optional[int] = None) -> Optional[Dict]:
+    ...
+
+# Multiple return types
+def parse_vote(self, vote_str: str) -> Tuple[bool, str]:
+    """Returns (success, error_message)"""
+    ...
+
+# Generic types
+def get_batch(self, ids: List[int]) -> Dict[str, Any]:
+    ...
+```

.mindmodel/patterns/streamlit.yaml

@@ -0,0 +1,225 @@
+# Streamlit Patterns
+
+## Session State Initialization
+
+Always initialize session state at the start of the main function:
+
+```python
+# app.py
+import streamlit as st
+
+def main():
+    # Initialize all session state variables
+    if "session_id" not in st.session_state:
+        st.session_state.session_id = None
+    if "current_motion_index" not in st.session_state:
+        st.session_state.current_motion_index = 0
+    if "motions" not in st.session_state:
+        st.session_state.motions = []
+    if "show_results" not in st.session_state:
+        st.session_state.show_results = False
+    
+    # Rest of app...
+```
+
+## Page Configuration
+
+Set page config at the top of each page file:
+
+```python
+# pages/1_Stemwijzer.py
+import streamlit as st
+
+st.set_page_config(
+    page_title="Stemwijzer",
+    page_icon="🗳️",
+    layout="centered",
+)
+
+from explorer import build_mp_quiz_tab
+build_mp_quiz_tab("data/motions.db")
+```
+
+## Thin Page Wrapper Pattern
+
+Pages delegate to shared functions in main modules:
+
+```python
+# pages/2_Explorer.py
+import streamlit as st
+
+st.set_page_config(
+    page_title="Explorer",
+    page_icon="🔭",
+    layout="wide",
+)
+
+from explorer import build_explorer_tab
+build_explorer_tab()
+```
+
+```python
+# explorer.py
+def build_explorer_tab():
+    st.header("🔭 Politiek Explorer")
+    
+    tab1, tab2, tab3 = st.tabs([
+        "Compass", 
+        "Trajectories", 
+        "Zoeken"
+    ])
+    
+    with tab1:
+        render_compass()
+    with tab2:
+        render_trajectories()
+    with tab3:
+        render_search()
+```
+
+## Sidebar Pattern
+
+Use sidebar for configuration and navigation:
+
+```python
+# app.py
+def main():
+    with st.sidebar:
+        st.header("Instellingen")
+        
+        motion_count = st.slider(
+            "Aantal moties",
+            min_value=5,
+            max_value=25,
+            value=10,
+        )
+        
+        policy_area = st.selectbox("Beleidsgebied", config.POLICY_AREAS)
+        
+        if st.button("Start Nieuwe Sessie"):
+            start_new_session(motion_count, policy_area)
+```
+
+## Callback Pattern for State Updates
+
+Use callbacks to handle user interactions:
+
+```python
+def on_motion_vote(motion_id: int, vote: str):
+    """Callback when user votes on a motion."""
+    st.session_state.user_votes[motion_id] = vote
+    
+    # Move to next motion
+    if st.session_state.current_motion_index < len(st.session_state.motions) - 1:
+        st.session_state.current_motion_index += 1
+    else:
+        st.session_state.show_results = True
+    
+    st.rerun()
+
+# In UI
+col1, col2, col3 = st.columns(3)
+with col1:
+    st.button("👍 Voor", on_click=on_motion_vote, args=(motion_id, "Voor"))
+with col2:
+    st.button("👎 Tegen", on_click=on_motion_vote, args=(motion_id, "Tegen"))
+with col3:
+    st.button("❓ Onthouden", on_click=on_motion_vote, args=(motion_id, "Onthouden"))
+```
+
+## Container Pattern for Dynamic Content
+
+Use containers for dynamic rendering:
+
+```python
+def show_motion_interface():
+    if not st.session_state.motions:
+        st.warning("Geen moties geladen")
+        return
+    
+    current_idx = st.session_state.current_motion_index
+    motion = st.session_state.motions[current_idx]
+    
+    with st.container():
+        st.subheader(f"Motie {current_idx + 1} van {len(st.session_state.motions)}")
+        st.markdown(f"**{motion['title']}**")
+        st.caption(f"📅 {motion['date']} | 🏷️ {motion['policy_area']}")
+        
+        if motion.get("layman_explanation"):
+            st.info(motion["layman_explanation"])
+        
+        # Voting buttons...
+```
+
+## Expander Pattern for Details
+
+Use expanders for collapsible content:
+
+```python
+with st.expander("Meer details"):
+    st.markdown(f"**Beschrijving:** {motion.get('description', 'N/A')}")
+    
+    if motion.get("voting_results"):
+        results = json.loads(motion["voting_results"])
+        st.json(results)
+```
+
+## Form Pattern for Batch Updates
+
+Use forms for multiple related inputs:
+
+```python
+with st.form("session_settings"):
+    st.subheader("Sessie Instellingen")
+    
+    col1, col2 = st.columns(2)
+    with col1:
+        count = st.number_input("Aantal moties", min_value=5, max_value=25)
+    with col2:
+        area = st.selectbox("Beleidsgebied", config.POLICY_AREAS)
+    
+    submitted = st.form_submit_button("Start Sessie")
+    if submitted:
+        start_session(count, area)
+```
+
+## Caching Pattern
+
+Cache expensive computations:
+
+```python
+@st.cache_data(ttl=3600)  # Cache for 1 hour
+def load_party_positions(window_id: str) -> Dict:
+    """Load party positions from database."""
+    return db.get_party_positions(window_id)
+
+@st.cache_resource
+def init_database():
+    """Initialize database connection."""
+    return MotionDatabase(config.DATABASE_PATH)
+```
+
+## Home Page Pattern
+
+Landing page with navigation:
+
+```python
+# Home.py
+import streamlit as st
+
+st.set_page_config(
+    page_title="Motief: de stematlas",
+    page_icon="🗺️",
+    layout="centered",
+)
+
+def main():
+    st.title("🗺️ Motief: de stematlas")
+    st.markdown("**Motief** brengt de Nederlandse Tweede Kamer in kaart...")
+    
+    col1, col2 = st.columns(2)
+    with col1:
+        st.page_link("pages/1_Stemwijzer.py", label="Open Stemwijzer", icon="🗳️")
+    with col2:
+        st.page_link("pages/2_Explorer.py", label="Open Explorer", icon="🔭")
+```

.mindmodel/stack/stack.yaml

@@ -0,0 +1,41 @@
+# Tech Stack
+
+## Runtime & Language
+- **Python ≥3.13** (type: runtime)
+- Streamlit (type: web framework) - multi-page app: Home, Stemwijzer, Explorer (4 tabs)
+
+## Data Layer
+- **DuckDB** (type: database) - 9 tables: motions, mp_votes, svd_vectors, mp_party_history, etc.
+- **ibis** (type: ORM) - DuckDB backend for Pythonic SQL
+- Query mode: duckdb:// path or :memory: (see database.py:50-51)
+
+## ML / Analytics
+- **scikit-learn** (type: ML) - clustering, Procrustes alignment
+- **UMAP** (type: dimensionality reduction) - 2D political compass projection
+- **scipy** (type: scientific computing) - spatial/alignment algorithms
+- **numpy** (type: numerical computing) - array operations
+
+## Visualization
+- **Plotly** (type: charting) - dual-layer interactive charts (scatter + annotations)
+
+## Key Source Files
+| File | Purpose |
+|------|---------|
+| `database.py` | MotionDatabase singleton, DuckDB connection, 9-table schema |
+| `explorer.py` | Explorer page with 4 tabs (Motion, MP, Party, Evolution) |
+| `explorer_helpers.py` | Pure helper functions, Plotly chart builders, coordinate computation |
+| `analysis/` | SVD pipeline, UMAP projection, clustering algorithms |
+| `pipeline/` | Data fetch → transform → store pipeline |
+| `pages/1_🗳️_Stemwijzer.py` | Quiz page (thin wrapper) |
+| `pages/2_🔍_Explorer.py` | Explorer page (thin wrapper) |
+| `config.py` | Dataclass Config pattern |
+
+## Database Tables
+- `motions` - parliamentary motions with id, title, date, category
+- `mp_votes` - individual MP votes on motions (1/0/-1)
+- `svd_vectors` - SVD-computed political positions (entity_id, window, vector_2d)
+- `mp_party_history` - MP-to-party mappings over time
+- `party_centroids` - aggregated party positions
+- `windows` - time period definitions
+- `mp_trajectories` - MP position changes across windows
+- Plus 2 additional tables (exact names vary)