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Ops readiness audit

Skill VictorAurelius/claude-starter-kit/skills/quality/ops-readiness-audit

Dùng khi user nói 'ops audit', 'production ready?', 'kiểm tra ops', 'deploy checklist', 'monitoring check', hoặc trước GA release. Production operations readiness /100.From its SKILL.md

Install
npx -y skills add VictorAurelius/claude-starter-kit --skill ops-readiness-audit

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
  • runs commandsInstructs the agent to run 5 commands, including `grep -rn "actuator\|prometheus\|metrics\|health" --include="*.yml" --include="*.yaml" \ | grep -v node_modules | grep -v target | head -30` and 4 more.

SKILL.md

5.0 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it

/ops-readiness-audit — Production Operations Readiness

Score /100. Verify the platform is ready for production operations: monitoring, logging, backup, alerting, deployment.

Process

1. Check Infrastructure Config

# Monitoring endpoints (broad scope — catches all submodules + infrastructure)
grep -rn "actuator\|prometheus\|metrics\|health" --include="*.yml" --include="*.yaml" \
  | grep -v node_modules | grep -v target | head -30

# Logging config (broad scope)
grep -rn "logging\.\|logback\|log4j\|winston\|pino" --include="*.yml" --include="*.xml" --include="*.ts" \
  | grep -v node_modules | grep -v target | head -20

# Backup/DR docs
ls documents/guides/*backup* documents/guides/*disaster* documents/guides/*recovery* 2>/dev/null

# Helm/k8s health probes
grep -rn "livenessProbe\|readinessProbe\|startupProbe" infrastructure/ | head -10

# Alert rules
ls infrastructure/*/alerting* infrastructure/*/alerts* 2>/dev/null

2. Primacy: bug-finding > scoring (BLOCKING)

An audit's purpose is to surface ops-operational gaps the dev team cannot trust other layers to catch. A 60/100 D score with hidden P0 gaps (no restore drill, no PII scrubber, no alert rules) is WORSE than 40/100 listing every gap honestly. Per .claude/rules/audit-skill-rubric-ops-readiness-audit.md §4.

Rules for every audit run:

  1. Enumerate ALL §3 sub-checks per category. NEVER skip "obviously fine."
  2. Each sub-check returns: PASS / FAIL / N/A-with-reason / ❓ UNCHECKED. No partial credit.
  3. Final output starts with bug list (every FAIL surfaces) BEFORE the score.
  4. Score is descriptive only; audit-level verdict = FAIL if ANY P0 sub-check FAILS.
  5. If audit time-budget runs out, mark ❓ UNCHECKED — do NOT default to PASS.

3. Score 5 Categories with per-check rubric

Every category binds to a per-check pass/fail rule. Within each 20-pt category: any P0/P1 sub-check FAIL caps category total ≤ 16/20.

#Category (20pts)Per-check rubric file
1Monitoring & Observability.claude/rules/audit-skill-rubric-ops-readiness-audit.md §2.1 (6 sub-checks, per-check pass/fail)
2Logging Standards.claude/rules/audit-skill-rubric-ops-readiness-audit.md §2.2 (6 sub-checks, per-check pass/fail)
3Backup & Recovery.claude/rules/audit-skill-rubric-ops-readiness-audit.md §2.3 (6 sub-checks, per-check pass/fail)
4Alerting.claude/rules/audit-skill-rubric-ops-readiness-audit.md §2.4 (6 sub-checks, per-check pass/fail)
5Deployment Pipeline.claude/rules/audit-skill-rubric-ops-readiness-audit.md §2.5 (6 sub-checks, per-check pass/fail)

Per-check scoring (all 5 categories)

For each Category N:

  1. Walk through every §2 sub-check in the bound rule.
  2. Mark each sub-check PASS / FAIL / N/A-with-reason / ❓ UNCHECKED (no partial credit).
  3. Score = 20 - (failed_P0_count * 6) - (failed_P1_count * 3) - (failed_P2_count * 1), floor 0; cap 20 if all PASS.
  4. If ANY P0 sub-check fails → category total CAPPED at 16/20 AND audit-level verdict = FAIL regardless of total score.
  5. Each FAIL surfaces in the audit-report bug list per §2 primacy.

Legacy scoring narrative: reference/scoring-guide.md retained for backward-compat only — the bound rule §2 IS the canonical rubric.

4. Output

Save to documents/audits/ops-readiness-audit-[date].md

Context Management

Token budget ~25-35K. Kiểm soát:

  1. Grep infrastructure files| head -20 per grep. Infrastructure files nhiều nhưng config sections lặp lại.
  2. Helm values — Chỉ đọc security-relevant keys (resources, probes, securityContext), không đọc full values.yaml.
  3. IaC — Chỉ check state backend config + resource count, không đọc full .tf files.
  4. Doc existence check — Dùng ls thay vì cat cho backup/DR docs. Chỉ đọc nội dung nếu cần verify chi tiết.

Gotchas

  • Spring Boot Actuator may be enabled but endpoints not exposed — check management.endpoints.web.exposure
  • Prometheus metrics need /actuator/prometheus endpoint AND scrape config in k8s
  • Message broker monitoring (RabbitMQ/Kafka): separate from app monitoring — check the broker's management plugin/exporter
  • Object storage: backup strategy different from the relational DB — object storage vs relational
  • If you have multiple microservices, each needs an independent health check
  • IaC state: must be remote (managed object-store bucket), not local
  • Multi-module scope — narrow grep on a single module may miss submodule config files; prefer broad --include="*.yml" from repo root.

Skill Contents

  • reference/scoring-guide.md — Detailed rubric per category

What ships with it: 1 file

4.1 KB alongside SKILL.md

reference/

Gives 0 of the 12 instructions most ship operate skills give in ~1.3k tokens

Counted across 1,077 of the 1,713 authors here whose files we hold, read 2026-09-06

  • Create GitHub releasein 44 of 1077, across 43 files
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  • Update the CHANGELOG for new releasesin 19 of 1077

Said here and by no other author read

  • Enumerate all sub-checks per category
  • Mark each sub-check pass, fail, or unchecked
  • List every fail in the bug list
  • Fail the audit if any p0 sub-check fails
  • Save the output to the audits directory

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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