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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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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.
Audit every ai/ file for gaps, stale placeholders, and inconsistencies after cold-start. Produces a prioritized findings report.
Diagnostic gate that checks AGENTS.md and AGENTS.md for completeness, consistency, and stale artifacts — run right after /cold-start and before /add-feature. Read-only; produces a findings report.
Typecheck and run the full test suite, and report failures concisely
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 (AGENTS.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].