This release adds 2 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
Summary
AI summaryAdded 88 pytest tests covering core modules and updated pyproject.toml for test discovery.
Full changelog
What's New
88 pytest tests covering Flaiwheel's core modules:
Quality Checker (test_quality.py — 27 tests)
- Clean repo validation (score, no false positives)
- Placeholder README skip logic (both
check_file()andcheck_all()paths) - Bugfix validation (required sections, missing section detection)
- Test case validation (required sections, missing section detection)
- Content pre-validation (
check_content()for bugfix and test categories) - Category detection for all 7 categories + default
- Orphan file detection (FLAIWHEEL_TOOLS.md whitelisting, root file flagging)
Indexer (test_indexer.py — 16 tests)
- Document type registry completeness
_detect_type()for all path patterns (parametrized, 15 cases)- Heading-based chunking (section splitting, metadata, edge cases)
- Chunk ID determinism and uniqueness
index_single()+ search round-trip- Type-filtered search
- Empty index behavior
Health Tracker (test_health.py — 15 tests)
record_search()hit/miss counting, per-tool trackingrecord_quality()score and issue countsrecord_index()success and failure statesrecord_skipped_files()list managementis_healthyproperty behavior- Thread safety under 1000 concurrent writes (10 threads × 100 ops)
MCP Server Tools (test_server.py — 22 tests)
- All 7 write tools (bugfix, architecture, API, best-practice, setup, changelog, test case)
- Changelog empty section guard
- Path traversal detection
- Search tools (docs, bugfixes, by_type, tests) — empty and populated
- Health metric recording from search calls
validate_doc()for valid/invalid bugfix and test contentget_index_stats()outputcheck_knowledge_quality()output
Other
pyproject.toml: added[tool.pytest.ini_options]withtestpaths = ["tests"]README.md: addedpytestto development instructions
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About dl4rce/flaiwheel
Self-hosted memory and governance layer for AI coding agents. 28 MCP tools with structured knowledge capture, hybrid search (semantic + BM25 + cross-encoder reranking), behavioral documentation nudges, cold-start codebase analyzer, and git-native storage. Single Docker container, zero cloud dependencies.
Related context
Beta — feedback welcome: [email protected]