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agent-navigabilitylisted

Audit a codebase for how easily a coding agent can navigate it, and propose structural fixes. Use this whenever an agent keeps re-exploring the same code, burns context finding where things live, edits the wrong file, or misses call sites it should have found; when reviewing structure, naming, module boundaries, or type usage for legibility rather than correctness; when onboarding cost is high for agents or new engineers; or when someone asks why agent runs on this repo are slow, expensive, or unreliable. Also use for requests like "restructure this for agents", "why does it keep missing files", "review our naming", or planning a refactor whose goal is comprehension rather than behaviour. Includes a migration mode for repo-wide restructuring such as separating client from server, splitting a monolith, or changing the top-level layout, which produces a phased plan rather than a findings list.
arndvs/ctrlshft · ★ 0 · AI & Automation · score 64
Install: claude install-skill arndvs/ctrlshft
# Agent navigability audit Every fresh agent session re-derives where things live. That cost is paid on every run, forever, and it scales with how many agents you run rather than how many engineers you have. A structure that's merely tolerable for a team that already knows it can be genuinely expensive for something that doesn't. The test throughout: **can an agent find the right file without reading the wrong ones?** Not "is this well designed" — a clean architecture can still be unnavigable, and a messy one can be easy to search. Legibility is a separate axis from quality, and this skill only audits legibility. Findings here are structural. If the question is about runtime output, error handling, or observability, use `logging-audit` instead — that's the behavioural half of the same problem. --- ## Step 1: Navigate it yourself first Don't read the repo and form opinions. **Attempt a real task and watch where you struggle.** Pick something plausible — "add a field to the main entity and thread it through", "find every place that writes to storage", "add an endpoint like the existing ones" — and note, concretely: - Which files you opened that turned out to be irrelevant - Where you had to guess, and what you guessed from - Searches that returned too much to be useful - Points where you couldn't tell which of several similar files was the live one That list *is* the finding set. Structural advice derived from reading a tree is generic and mostly unactionable; advice de