claude-skills is a large collection of reusable skills, commands, plugins, and supporting resources for coding agents across engineering, business, research, compliance, and productivity work. It is used by people who want agents such as Claude Code, Codex, Gemini CLI, or Cursor to follow specialized workflows. The catalogue contains selected skills and settings from the collection.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add alirezarezvani/claude-skills --skill chief-ai-officer-advisorgit clone --depth 1 https://github.com/alirezarezvani/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alirezarezvani/claude-skills/chief-ai-officer-advisor)<a href="https://agentmods.dev/skills/alirezarezvani/claude-skills/chief-ai-officer-advisor"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-skills/chief-ai-officer-advisor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alirezarezvani/claude-skills/chief-ai-officer-advisor"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-skills/chief-ai-officer-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 1 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00148 | $0.03602 |
| Opus 5.5 | $0.00059 | $0.01441 |
| Sonnet 5.5 | $0.00030 | $0.00720 |
| Haiku 4.5 | $0.00015 | $0.00360 |
Grade A, and why
chief-ai-officer-advisor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chief AI Officer Advisor
Strategic AI leadership for startup CAIOs and founders without one. Four decisions, no AI hype:
- Should we use an API, fine-tune, or build our own? — model build-vs-buy with 3-year TCO
- Is this AI use case high-risk under regulation, and how do we govern it? — EU AI Act + NIST AI RMF + US state patchwork
- When do we switch from API to self-hosted, and at what cost? — token economics with breakeven analysis
- What AI role do we hire next? — stage-to-role map (AI engineer ≠ ML engineer ≠ research scientist)
This skill does not cover tactical AI/ML engineering. For RAG implementation, agent design, prompt engineering, eval infrastructure, model deployment, or cost optimization, see engineering/rag-architect/, engineering/agent-designer/, engineering/prompt-governance/, engineering/self-eval/, engineering/llm-cost-optimizer/.
Keywords
CAIO, chief AI officer, AI strategy, model selection, foundation model, fine-tuning, RLHF, DPO, LoRA, QLoRA, build vs buy, AI build-vs-buy, model risk tier, EU AI Act, AI Act Article 6, Article 9, Article 10, Annex III, prohibited AI, high-risk AI, NIST AI RMF, AI risk management framework, NYC Local Law 144, Colorado SB 21-169, Illinois HB 53, model card, eval set, eval harness, hallucination rate, jailbreak risk, prompt injection, AI red team, AI safety, alignment, model lifecycle, model registry, API-to-self-hosted breakeven, GPU economics, A100, H100, inference cost, fine-tuning cost, AI team, AI engineer, ML engineer, research scientist, MLOps, AI platform
Quick Start
# Decision A: API vs fine-tune vs build
python scripts/model_buildvsbuy_calculator.py # embedded customer-support sample
python scripts/model_buildvsbuy_calculator.py path/to/use_case.json
# Decision B: Risk classification under EU AI Act + US state laws
python scripts/ai_risk_classifier.py # embedded hiring-AI sample
python scripts/ai_risk_classifier.py path/to/use_case.json
# Decision C: API vs self-hosted economics
python scripts/ai_cost_economics.py # embedded 5M tokens/day sample
python scripts/ai_cost_economics.py path/to/workload.json
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/ai_cost_economics.md 10 KB
- references/ai_risk_governance.md 13 KB
- references/ai_team_org_evolution.md 12 KB
- references/model_buildvsbuy_strategy.md 7.9 KB
- scripts/ai_cost_economics.py 16 KB runs code
- scripts/ai_risk_classifier.py 20 KB runs code
- scripts/model_buildvsbuy_calculator.py 17 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed · +236 lines · +148 tokens per session 4d183b3ff5db
- 1mo ago First seen · 1 lines · 0 tokens per session scan A f14a7a1458ba
chief-ai-officer-advisor is a skill published in the GitHub repository alirezarezvani/claude-skills (28,852 stars, last pushed today), licensed MIT. It adds 148 tokens to every session and 3,602 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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