/cs:caio-review <plan> — Eval-demanding Chief AI Officer interrogation of any plan that involves AI: model selection, risk classification, cost economics, or AI hiring. Use when shipping an AI feature without an eval set, choosing between API, fine-tune, and self-hosted, or classifying a use case under the EU AI Act.
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。
Command: /cs:caio-review <plan>
The eval-demanding CAIO pressure-tests any plan that involves AI. Six questions before any AI feature ships, any multi-year vendor commitment, or any AI team expansion.
No eval set = no ship. Before any AI feature deploys, define the eval criteria.
Every AI feature has a failure mode. Plan for it.
Run ai_risk_classifier.py if any EU residents are affected OR domain is regulated.
Run model_buildvsbuy_calculator.py for the specific use case.
Run ai_cost_economics.py for the workload.
Map AI capability to specific role. Founders confuse AI engineer / ML engineer / research scientist.
# 1. Model selection check
python ../../../c-level-advisor/skills/chief-ai-officer-advisor/scripts/model_buildvsbuy_calculator.py use_case.json
# 2. Regulatory classification
python ../../../c-level-advisor/skills/chief-ai-officer-advisor/scripts/ai_risk_classifier.py use_case.json
# 3. Cost projection
python ../../../c-level-advisor/skills/chief-ai-officer-advisor/scripts/ai_cost_economics.py workload.json
# CAIO Review: <plan>
**Date:** YYYY-MM-DD
## The Decision Being Made
[one sentence — which CAIO decision: model selection | risk classification | economics | next hire]
## Eval Discipline
- Eval set committed: yes/no
- SLO defined: <metric> < <threshold>
- Fallback behavior: <one line>
## Model Selection (if applicable)
- Recommended: API / FINE_TUNE / BUILD
- 3-year TCO: $X (chosen path) vs $Y (alternatives)
- Breakeven: <volume>
## Risk Classification (if applicable)
- EU AI Act tier: PROHIBITED / HIGH / LIMITED / MINIMAL
- Conformity assessment required: yes/no
- US state triggers: [list]
- Required controls open: N
## Cost Economics (if applicable)
- Monthly cost at current volume: $X
- Breakeven for self-hosted migration: <volume>
- Migration cost if applicable: $X (3-6 months)
## Org (if applicable)
- Next hire: <role>
- Why this, not the alternative: <one line>
- Prerequisite hires in place: yes/no
## Verdict
🟢 SHIP | 🟡 SHARPEN | 🔴 BLOCK
## Next Steps
[3 concrete actions]
/cs:cdo-review — for any training-data implications/cs:gc-review — for AI vendor contracts, output liability, training-data licensing/cs:ciso-review — for prompt injection / jailbreak / training-data poisoning threat model/cs:cfo-review — for multi-year vendor or GPU commitment TCOcs-chro-advisor agent — for AI team hires (comp, ladder, leveling)/cs:decide — log the verdict/cs:freeze 60 — on multi-year AI commitmentscs-caio-advisorchief-ai-officer-advisor../../../c-level-advisor/skills/chief-data-officer-advisor/ (training data rights, data strategy)Version: 1.0.0
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。
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。
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。
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。
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。
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。
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。