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.
Review code for bugs, complexity, unused symbols, and structural issues using AST-aware analysis. Use when reviewing PRs, checking code quality, finding dead code, analyzing function complexity, auditing a codebase, or checking for type errors. Each call reports the kinds it modeled in `modeled_kinds` — that is the honest coverage signal; the supported-language list is whatever act ships.
Generate a robust, idempotent work-loop tracker — the single resumable state file that drives a large implementation program through plan → implement → review cycles with self-tracking, found-issue capture, and remediation discipline. Use whenever the user wants to execute a large or multi-item implementation systematically; triggers include "create a work loop", "set up a tracker", "make this resumable", "execution harness", "work through this spec item by item", or any time one or more approved specs need to be implemented across many sessions or by many agents and progress must survive context loss. Also drives and resumes the **quality loop** — a.k.a. "continuous quality", "the quality ratchet", "the architecture ratchet" — which maps to the architecture-audit → architectural-refactoring → verify-refactor skill cycle; triggers include "run the quality loop", "set up a quality ratchet", "keep auditing and refactoring", "continuously improve architecture".