Walk the B1-B19 AI-to-AI blind-spot catalog systematically. Use during the audit pipeline AFTER hard-stops and Tambon hunt and BEFORE the 13 domain audits. Output: PRESENT / NOT PRESENT for each B-class with evidence. Findings flow into the appropriate domains.
Audit the architecture and code quality domain — module boundaries, abstraction layers, code organization, naming, documentation. Run as part of /audit Phase E.
Audit the database and data layer — schema design, query patterns, migrations, indexing, RLS, soft-delete, transactions. Run as part of /audit Phase E.
Audit the UI/UX and accessibility domain — error states, loading states, form validation, keyboard nav, ARIA, color contrast, mobile responsiveness. Run as part of /audit Phase E.
Audit the reliability domain — error handling, retries, idempotency, race conditions, partial failures, timeouts, graceful degradation. Run as part of /audit Phase E.
Audit the legal/privacy/compliance signals — privacy policy alignment, data retention, GDPR/CCPA basics, cookie consent, export/delete capabilities. Run as part of /audit Phase E.
Audit the dev experience and maintainability — local setup, documentation, test quality, CI feedback time, debuggability. Run as part of /audit Phase E.
Audit the cost and billing risk domain — runaway loops, unbounded LLM/API calls, missing rate limits on paid services, infrastructure cost amplifiers. Run as part of /audit Phase E.
Audit the gap between demo-quality and production-quality — hardcoded test data, dev-only configurations shipped, missing prod hardening. Run as part of /audit Phase E.
Audit what a normal production app at this scale would have but is absent — health checks, error tracking, feature flags, audit logs, on-call. Run as part of /audit Phase E.
Audit code integrity and coherence — duplication, hallucinated references, Tambon signatures, spec drift, Frankenstein patterns, mystery code. THIS DOMAIN incorporates findings from the Tambon hunt and most of the blind-spots walk. Run as part of /audit Phase E.
Generate a detailed AI fix prompt for a specific audit finding. Use when the user asks "/audit-fix F-X.Y" or "give me the fix prompt for finding N." Produces a complete prompt the user can hand to a fresh AI session (Claude Code, Cursor, ChatGPT) to remediate the finding with verification and rollback steps.
Walk the H1-H11 hard-stops catalog systematically against an audit scope. Use as the FIRST audit phase after audit-method completes. Runs detection commands for each hard stop class and reports FOUND / NOT FOUND with evidence. If any hard stop is found, the audit verdict locks to 🛑 DO NOT LAUNCH.
Orchestrate the full audit improvement cycle: audit, roadmap, remediation, rerun, delta comparison, and skill patching for missed findings until convergence or a terminal blocked state.
Run the methodology setup phase of a technical audit — fingerprint the stack, inventory the repository, and produce a system map. Use this BEFORE running any audit domains. Output: detected stack, repo summary, and high-level architecture in 3-5 paragraphs. No findings yet.
Conduct a full technical due diligence audit of a vibe-coded codebase. Use when the user types /audit, asks for a "full audit," asks for a "due diligence review," asks "is this codebase ready to ship?", or asks for a comprehensive code review of an entire repository (not a single PR). Coordinates the 13 domain skills…
Hunt the three Tambon LLM-failure-mode signatures (Hallucinated Object, Wrong Attribute, Silly Mistake) across an audit scope. Use during the audit pipeline AFTER hard-stops and BEFORE blind-spots. Output: counts per signature, top occurrences, density per 1000 LoC. Findings flow into Domain 13 (Code Integrity).
Run a fail-closed end-to-end project hardening cycle: static audit, exhaustive real-browser validation, semantic screenshot review, multi-role/security/visual-regression probes, isolated remediation, and re-verification. Use when the user asks to battle-test or prove production readiness. Default is the full cycle…
Audit websites, web apps, mobile apps, design systems, and user flows against the full public Checklist Design corpus. Use for comprehensive or targeted product/UI/UX audits, source-linked inspiration comparisons, evidence-backed scoring, and remediation plans.
Multi-LLM debate orchestration (Claude vs Codex vs Gemini) with rounds + synthesis.
★not rated 41 11d agoA23 tokens
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: