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Dry-run the add-feature workflow for a proposed feature — friction report and per-phase readiness score, without writing code.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
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.
| name | perform-feature-add-simulation |
| description | Dry-run the add-feature workflow for a proposed feature — friction report and per-phase readiness score, without writing code. |
| disable-model-invocation | true |
Simulate adding the feature the user names — WITHOUT writing a single line of code. This is a pre-flight check of both the plan and the knowledge layer.
frozen or ? file ⇒ blocked pending human approval.A friction report in chat (and, if asked, saved to ai/analysis/audit-reports/): per-phase score with the specific missing knowledge that caused friction, total estimated context cost, and a go / no-go recommendation. Knowledge gaps found here are the cheapest bugs you will ever fix — file each as an audit TODO.