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Use when you need to find the riskiest code in a repository — where bugs are most likely to live — by combining git churn, complexity, co-change coupling, and ownership concentration into one ranked, explained list.
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Based on SOC occupation classification
Audit whether an AI agent edit to a file is safe — composes secret-surface, taint-flow, change-impact, and API-surface analysis into an agent-edit safety report. Use before letting an agent modify a sensitive or high-blast-radius file.
Execute structural decompositions based on an architectural analysis report. Use when breaking circular dependencies, splitting god classes, reducing coupling between modules, extracting interfaces at seam boundaries, or executing any large-scale structural change identified in an architectural analysis. Requires a prior architecture audit (the architecture-audit skill) that produced project-map.md and a run report.
Use when asked to audit architecture, produce a comprehensive architectural overview, get the full structural picture of a codebase, assess overall health and porting readiness, find module boundaries, circular dependencies, coupling hotspots, dead code, or code patterns. Depth 3 — full audit with hypothesis-driven investigation. Optionally enriches the structural audit with runtime and git evidence (coverage, churn, co-change coupling, ownership) when those overlays are available. Replaces the architectural-analysis and architecture-audit-plus skills.
Use when looking for extraction candidates, planning a module split, analyzing module boundaries, or before decomposing a large component. Also use when asked "where should I split this?" or "find natural module boundaries". Depth 2 — investigate. Produces extraction candidates with cut costs, layer violations, interface width assessment, orphan types, and a recommended decomposition sequence.
Use before modifying a file or symbol, or when asked "what breaks if I change X?". Depth 0 — fast, no follow-up queries, returns immediately. Two modes: inline (no artifacts, default for agent-initiated use) and artifact (writes to docs/act/, triggered for human-initiated requests or Critical risk verdicts).
Traverse large repositories efficiently using act's query tools. Use when exploring unfamiliar code, mapping dependencies, understanding API surfaces, analyzing side effects before modifying functions, or following call chains across files. Avoids reading entire files by querying only the structure needed.
| name | where-bugs-live |
| description | Use when you need to find the riskiest code in a repository — where bugs are most likely to live — by combining git churn, complexity, co-change coupling, and ownership concentration into one ranked, explained list. |
Rank the code most likely to harbor defects by composing four signals. Bugs cluster where code changes often, is complex, is entangled with other code, and is owned by few people.
The git-overlay ops require a git repository with history. All are MCP tools (Architecture tier).
churn_hotspots (workspace mode, no file) to rank symbols by recency-weighted change frequency. High churn = actively-changing, defect-prone code.analyze_hotspots to rank files by composite complexity (cyclomatic, statements, nesting). Complex code hides bugs.co_change_clusters to find symbols that change together. Hidden coupling means a fix in one place needs a fix in another — a classic bug source.ownership_map to find low-bus-factor symbols. Code owned by one departed author is risky to touch.A ranked, explained risk list. Each item: symbol/file, the firing signals (churn score, complexity, co-change members, bus factor), and a one-line "why this is risky." Lead with the highest-confidence intersections (multiple signals agree).
Respect modeled_kinds: for grammars without symbol extraction, churn/co-change/ownership degrade to file-level — say so rather than implying symbol precision. Churn and ownership are git facts; complexity is a syntactic estimate.