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Holistic assessment of the AI knowledge layer on a 5-level maturity scale; flags agent-blocking gaps.
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Based on SOC occupation classification
| name | verify-ai-readiness |
| description | Holistic assessment of the AI knowledge layer on a 5-level maturity scale; flags agent-blocking gaps. |
| disable-model-invocation | true |
Assess how ready this repository is for agentic work. Read-only; output one report.
[inferred].[verified].
The minimum bar for letting an agent build features.Score each: entry files (CLAUDE.md/AGENTS.md), MODULE_MAP coverage & verification
ratio (% rows [verified]), FEATURE_MAP/CATALOG coverage, conventions, diagrams,
ai/lab/ activity. Evidence = file contents only; no speculation.
Write ai/analysis/audit-reports/<YYYY-MM-DD>-readiness.md: overall level, per-area
table (area · evidence · level), the SINGLE most valuable next action, and any
agent-blocking gaps (anything that would make a feature build unsafe today).
Tag the report [inferred].
Bootstrap the ai/ knowledge layer for a repo that has none — draft the MODULE_MAP, diagrams, and guide docs as [inferred] for a human to audit, touching no source code. Use when the maps are still placeholders or the user asks to cold-start, bootstrap, or onboard a repository.
Bootstrap the ai/ knowledge layer for a repo that has none — draft the MODULE_MAP, diagrams, and guide docs as [inferred] for a human to audit, touching no source code. Use when the maps are still placeholders or the user asks to cold-start, bootstrap, or onboard a repository.
Deep, judgement-based adversarial code audit — hunts for stale cross-references, unescaped interpolation, platform gaps, generated-file ownership conflicts, and cross-module consistency rot that no mechanical check can catch. Read-only; writes a dated findings report.
Kit-maintainer diagnostic (LOCAL-ONLY, not distributed) that audits the README and docs/ for staleness against the repo's real command/skill/CLI roster, stamped tree, and cross-doc consistency. Read-only; produces a severity-ranked findings report.
Run verification and drift checks on the AI knowledge-base to identify missing documentation or stale references.
Deep-mine the source code to discover implemented features; writes ai/analysis/FEATURE_CATALOG.md.