This release adds 2 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
Summary
AI summaryTwo-pass classifier improves cold-start classification quality with path heuristics and code‑specific embedding templates.
Full changelog
Improved: Cold-Start Classification Quality
Two-pass classifier in code_analyzer.py — no new dependencies, no Docker rebuild.
Pass 1 — Path heuristics (zero model cost)
High-confidence pattern matching on filename/path runs first:
| Pattern | Category |
|---|---|
| supabase/functions/*/index.ts | api |
| test_*, *.spec.*, */tests/* | tests |
| config, settings, docker, deploy | setup |
| utils, helpers, shared, lib | best-practices |
| error, retry, fallback | bugfix-log |
| main, server, router, handler, api, middleware | api |
Resolves ~60-70% of files with 0.9 confidence — no embedding call needed.
Pass 2 — Embedding fallback (code-specific templates)
For remaining files, uses new _CODE_CATEGORY_TEMPLATES tuned to what source code looks like (route handlers, assert statements, env vars) instead of the doc-oriented templates that caused changelog over-classification on large mixed codebases.
Upgrade
curl -sSL https://raw.githubusercontent.com/dl4rce/flaiwheel/main/scripts/install.sh | bash
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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]