Conciseness

The body is dense with operative content — commands, thresholds, verdict rules — and assumes Claude's competence rather than explaining what S3 or IAM is. It falls short of lean/anchor-5 due to narrative fleet-sweep anecdotes ('Each check below comes from a real fleet sweep in October 2026,' the 96-day-old-deploy story) and time-sensitive version/date details ('CVE-2026-66066,' 'Heroku-24 ships 8.15.1') that add tokens and will age, but well above the noticeably-verbose anchor-3.

Actionability

Nearly every section is copy-paste-ready: exact CLI commands with jq projections ('vercel api "/v6/deployments?projectId=<id>&target=production&limit=5" | jq ...'), API endpoints, concrete thresholds (libvips ≥ 8.13, keys older than 90 days, check the last 10–20 deploys), a redaction-safe host-extraction one-liner, and a validator invocation ('node references/validate-findings.mjs findings.json'). Specific examples cover the common cases across all three clouds and six PaaS platforms.

Workflow Clarity

The process is clearly sequenced — Authorization → Scope → Audit Categories → 'Verify, then record' steps 1–7 → Output Format → Boundaries — with explicit validation checkpoints and feedback loops: a refutation pass on every candidate before confirmation, 'write findings.json ... and fix until it passes' the validator, and re-run matching by fingerprint with re-reading rejected evidence. The verdict table defines exactly how to close each candidate, matching the anchor-5 pattern of sequence + explicit validation + error-recovery loops.

Progressive Disclosure

Structure is good: detailed material is one level deep in real, well-signaled files linked at point of use ([references/paas.md], findings-format.md, verification.md, severity-calibration.md, validate-findings.mjs, to-sarif.mjs), each verified present and appropriately scoped, plus a References section with external docs. It misses anchor 5 because the ~310-line body is itself fairly monolithic — the PaaS section's worked examples and the long verdict-table examples are inline detail that could partly live in the references, leaving SKILL.md closer to an overview.

Specificity

The description names concrete audit targets — 'misconfigurations, excessive permissions, stale or manual production deploys' — across nine named platforms, which is several specific capabilities with minor gaps. It stops short of anchor 5 because the core action is a single generic verb ('Audit... for... security gaps') rather than multiple distinct concrete actions.

Completeness

It explicitly answers both questions: the 'what' is 'Audit cloud infrastructure (AWS, GCP, Azure) and PaaS deployment platforms (Vercel, Netlify, Heroku, Render, Railway, Fly) for misconfigurations, excessive permissions, stale or manual production deploys, and security gaps,' and the 'when' is a full 'Use when the user mentions [...20 trigger phrases] or needs to review cloud or deployment-platform security' clause with concrete triggers — exactly the anchor-5 pattern.

Trigger Term Quality

The 'Use when' clause covers natural keywords comprehensively, from the expected ('cloud security,' 'AWS security,' 'S3 bucket') through platform synonyms ('Vercel security,' 'Heroku audit,' 'Supabase RLS') to conversational phrasings users would actually say ('is production built from main,' 'old vercel.app still live,' 'preview deployments exposed'). This matches the comprehensive-coverage anchor including synonyms and per-platform variants.

Distinctiveness Conflict Risk

The cloud/PaaS security-audit niche is clear and most triggers are distinct, but the trigger 'IAM audit' collides with the separate `iam-audit` skill this very skill cross-references for IAM deep-dives, creating minor overlap risk with a closely related sibling skill. Not score 5 (a trigger term actively shared with a sibling), clearly above score 3 (the fleet-deploy and platform-specific triggers are unmistakable).