本文へ移動
cccskills
無料GitHub で公開

compliance-readiness

/cs:compliance-readiness <program> — Multi-framework compliance officer 6-question forcing interrogation of any compliance program. Use before starting a new framework, planning the annual audit calendar, or preparing for certification stage 1.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md5.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

/cs:compliance-readiness — Compliance Officer Forcing Questions

Command: /cs:compliance-readiness <program>

The multi-framework compliance officer pressure-tests any compliance program. Six questions before any new-framework commitment, audit cycle planning, or certification readiness sign-off.

When to Run

  • Before adopting a new compliance framework
  • Before annual audit calendar finalization
  • Before certification stage 1 readiness sign-off
  • Before management review (Clause 9.3 across frameworks)
  • When evidence-collection effort has grown 50%+ year-over-year (a smell)
  • When an audit produced > 15% critical findings

The Six Compliance Officer Questions

1. Have you named every applicable framework?

No framework selector run, no defensible scope.

  • Run framework_selector.py with company profile
  • Forgetting a framework means rebuilding the audit program later
  • Pay attention to industry-specific overlays (financial: NYDFS, FINMA; healthcare: HIPAA, ISO 13485; AI: ISO 42001 + EU AI Act)

2. Where do the frameworks overlap, and what's the reuse leverage?

Single evidence -> N controls = the cornerstone of multi-framework efficiency.

  • Run cross_framework_mapper.py with enabled frameworks
  • HIGH-confidence mappings: same evidence; MEDIUM: existing + overlay; LOW: new artefact
  • Without overlap analysis, you'll collect the same access-review records 3 times

3. Who owns each artefact, and what's the reuse-leverage score?

Joint ownership without accountability is the most common cause of stale evidence.

  • Run evidence_pool_generator.py for the artefact inventory
  • HIGH-leverage artefacts (≥ 5 mappings) get built first
  • Each artefact needs one accountable owner
  • Stale evidence is an effective gap — even if the artefact existed historically

4. What's the audit calendar, and is auditor independence respected?

Surveillance audits stacking in the same week is a smell.

  • Use per-framework audit-plan tools (aims_audit_scheduler, isms_audit_scheduler, audit_schedule_optimizer)
  • Auditor cannot audit their own work (Clause 9.2 across all ISO standards)
  • For small teams: rotate auditors + occasional external auditor

5. What does a mock audit produce, and is the severity distribution healthy?

No mock audit, no readiness signal.

  • Run audit_simulator.py with framework + scope
  • Healthy distribution: ≥ 40% observation, ≤ 15% critical
  • All-critical findings = destructive audit OR genuinely failing program
  • All-observation findings = audit too superficial

6. What's the management review cadence across frameworks?

Each framework wants its own management review; an integrated review (per Annex SL) saves 5x exec time.

  • Schedule one quarterly cross-framework review covering all enabled frameworks' Clause 9.3 inputs
  • Inputs: risk register changes, open nonconformities, audit findings, incidents, drift, KPIs
  • Outputs: action items, resource decisions, scope adjustments

Workflow

# 1. Framework selection
python ../../skills/compliance-os/scripts/framework_selector.py profile.json

# 2. Cross-framework overlap
python ../../skills/compliance-os/scripts/cross_framework_mapper.py program.json

# 3. Evidence pool consolidation
python ../../skills/compliance-os/scripts/evidence_pool_generator.py program.json

# 4. Mock audit (per framework)
python ../../skills/compliance-os/scripts/audit_simulator.py scope.json

Output Format

# Compliance Readiness: <program>
**Date:** YYYY-MM-DD

## The Decision Being Made
[framework-set | audit-calendar | certification-readiness | evidence-consolidation]

## Framework Set
- Applicable: <list>
- Binding (regulations): <count>
- Certifiable: <count>
- Missing dependencies: <list>

## Cross-Framework Overlap
- Total merged controls in scope: N
- High-leverage artefacts (≥ 5 mappings): M
- Top reuse opportunities: <top 5 artefacts>

## Evidence Pool
- Artefacts in catalog: N
- High-leverage count: M
- Stale evidence rate: X%
- Unowned artefacts: K

## Audit Calendar
- Frameworks scheduled this year: <list>
- Auditor independence respected: Y/N
- Conflicts: <list>

## Mock Audit Results (per framework)
- <framework>: total findings N, critical X%, observation Y%, healthy distribution: Y/N

## Verdict
🟢 READY | 🟡 STAGE-2-CANDIDATE | 🔴 NOT-READY

## Top 3 Actions
[3 concrete next steps with owners + dates]

Routing

  • /cs:aims-audit — for ISO 42001-specific forcing questions
  • /cs:ai-act-readiness — for EU AI Act-specific forcing questions
  • /cs:ciso-review — for cybersecurity strategy
  • /cs:caio-review — for executive AI strategy
  • /cs:gc-review — for novel-case legal review
  • /cs:decide — to log the verdict
  • /cs:freeze 30 — on certification commitments (multi-year financial impact)

Related

  • Agent: cs-compliance-officer
  • Skill: compliance-os
  • Adjacent: ra-qm-team/skills/iso42001-specialist/, ra-qm-team/skills/eu-ai-act-specialist/, ra-qm-team/skills/information-security-manager-iso27001/, ra-qm-team/skills/soc2-compliance/, ra-qm-team/skills/gdpr-dsgvo-expert/

Version: 1.0.0

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Accessibility audit skill for scanning, fixing, and verifying WCAG 2.2 Level A and AA compliance across React, Next.js, Vue, Angular, Svelte, and plain HTML codebases. Use when auditing accessibility, fixing a11y violations, checking color contrast, generating compliance reports, or integrating accessibility checks into CI/CD pipelines.

日本語の概要は準備中です。原文の説明を表示しています。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," or "test this." For tracking implementation, see analytics-tracking.

日本語の概要は準備中です。原文の説明を表示しています。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

When the user needs to generate, iterate, or scale ad creative for paid advertising. Use when they say 'write ad copy,' 'generate headlines,' 'create ad variations,' 'bulk creative,' 'iterate on ads,' 'ad copy validation,' 'RSA headlines,' 'Meta ad copy,' 'LinkedIn ad,' or 'creative testing.' This is pure creative production — distinct from paid-ads (campaign strategy). Use ad-creative when you need the copy, not the campaign plan.

日本語の概要は準備中です。原文の説明を表示しています。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a PR, or when you suspect Claude is being too agreeable about code quality. Forces perspective shifts through hostile reviewer personas that catch blind spots the author's mental model shares with the reviewer.

日本語の概要は準備中です。原文の説明を表示しています。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

aeo

無料

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

日本語の概要は準備中です。原文の説明を表示しています。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping. Three decisions: whether an action needs a receipt, minting it, verifying it. Signing is delegated to the open-source OpenAgentOntology package. Not after-the-fact log analysis; not a hosted notary; not a legal opinion.

日本語の概要は準備中です。原文の説明を表示しています。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

alirezarezvani のスキルをすべて見る

このスキルの問題を報告する