tsa-refactor-queue

tsa-refactor-queue is a Codebase audits & code health skill for AI agents, published by aimasteracc in the tree-sitter-analyzer repository on GitHub. Skillspace rates tsa-refactor-queue D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Build a top-N prioritized refactoring queue by intersecting three signals: health grade (which files are F/D), temporal churn (which files change most often), and dead-code density (which files carry the most unreachable symbols). For each candidate the queue surfaces (a) the dimension that dragged the grade down, (b) the target symbol, (c) blast radius from `nav action=callers`, and (d) a concrete action — `split`, `delete dead`, or `extract`. Motivated by `docs/agent-tooling-gap-report.md` "Next High-Value Work" §5: use `health action=project` output to open focused refactoring slices for the current F-grade files, starting with low-coverage Language Plugin extractors and `api.py`. Use when: - "Where should I refactor next?" / "Build me a refactor queue" - Post-feature cleanup pass - Engineering planning: "what would 2 weeks of cleanup buy us?" - Re-grading after a sprint: "did the queue shrink?" Replaces: per-file `health action=file` loops + spreadsheet ranking (~25k tokens) with 3…

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

43

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