Migrate all repos into monorepo context folders

Bahn: aisupport, Analyse-O2C-C2S, awesome-bahn-mcp-servers, beam-mcp,
      Confluence_Bot, db-planet-mcp-server, O2C-Harness, project-audit,
      Projekt-KIQ-HP, teamlandkarte-mcp
Dhive: Jury-Voting
Privat: CV, NoteGraph (NOTE: NoteGraph needs complete redo after consolidation)
Shared: AI-Orchestrator, OrgMyLife, power_skills_and_more
Shared/references: symphony (read-only)

Bahn repos remain available as independent remotes - this monorepo
pulls them in via subtree, the originals are untouched.

bahn/teamlandkarte-mcp/.github/prompts/debug-matching.prompt.md

@@ -0,0 +1,45 @@
+---
+description: Debug matching issues — investigate why capacity matching produces unexpected results (wrong scores, missing candidates, expired searches).
+---
+
+$ARGUMENTS
+
+## Debugging Matching Issues
+
+### Common Issues
+
+**1. Unexpected scores (too high/low)**
+- Check `config.toml` weights: `[matching]` section has `role_weight` and `competence_weight`
+- Check similarity strategy: `matching.similarity.use_bm25_search` (BM25 vs embeddings)
+- BM25 scores 0.0 for non-overlapping tokens (not semantic — "ML" ≠ "Machine Learning")
+- Embedding similarity is cosine-based (0.0–1.0 range)
+
+**2. Missing candidates**
+- Check availability filtering: `date_start`/`date_end` may exclude valid candidates
+- Check `is_fully_available` filter — partial overlap candidates are excluded
+- Verify the candidate has a published capacity in the database
+
+**3. Expired/invalid search sessions**
+- Search cache TTL: 60 minutes (configurable in `[cache]`)
+- If `status=unknown_or_expired`: rerun `find_matching_capacities(...)` for fresh results
+- Never retry with a guessed search_id
+
+**4. Embedding failures**
+- Check Azure OpenAI connectivity and API key in `.env`
+- Check `azure_openai.embedding_batch_size` in config (default: 128)
+- Failure is strict: no heuristic fallback
+
+### Diagnostic Steps
+
+1. Check config: `cat config.toml` — verify weights, thresholds, similarity strategy
+2. Check logs: server logs show embedding calls, cache hits, query execution
+3. Validate requirements: use `validate_task_requirements(task_id)` to compare DB vs inferred
+4. Check cache state: SQLite embedding cache at path configured in `[embedding_cache]`
+5. Run with verbose: `uv run pytest -v tests/test_similarity.py` for similarity logic tests
+
+### Key Files
+- `src/teamlandkarte_mcp/matching/scorer.py` — scoring logic
+- `src/teamlandkarte_mcp/matching/similarity.py` — similarity computation
+- `src/teamlandkarte_mcp/matching/matcher.py` — orchestration
+- `src/teamlandkarte_mcp/cache/` — all cache layers
+- `config.toml` — runtime configuration