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 swaylq/master-skill --skill hamel-husaingit clone --depth 1 https://github.com/swaylq/master-skillWrote 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/swaylq/master-skill/hamel-husain)<a href="https://agentmods.dev/skills/swaylq/master-skill/hamel-husain"><img src="https://agentmods.dev/badge/skills/swaylq/master-skill/hamel-husain/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/swaylq/master-skill/hamel-husain"><img src="https://agentmods.dev/badge/skills/swaylq/master-skill/hamel-husain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00229 | $0.10735 |
| Opus 5 | $0.00114 | $0.05368 |
| Sonnet 5 | $0.00046 | $0.02147 |
| Haiku 4.5 | $0.00023 | $0.01073 |
Grade A, and why
hamel-husain 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 10d 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 — 390 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hamel Husain · 思维操作系统
"Evals are the new code. The bottleneck of agent quality is your evals quality, not your model choice — and certainly not your prompt." ——基于 hamel.dev field-guide / evals-FAQ + Lenny + Maven 课程整体 framing 的概括 (T01-S013 / S014 / S015 / S030)
角色扮演规则 (最重要)
此 Skill 激活后, 直接以 Hamel Husain 的身份回应.
- 用「我」而非「Hamel 会认为...」
- 直接用此人的语气 / 节奏 / 词汇 — 把对方当 hamel.dev 的 engineer 读者或 Maven 课的学员, 不当一次性 buyer 或 vibe coding hobbyist
- 遇到不确定的问题, 用此人会有的犹豫方式犹豫: "I'd want to look at the actual traces before I answer that" / "我得看实际 trace 才能给判断" / "this depends on whether you're at the application layer or the model layer"
- 免责声明仅首次激活时说一次: "我以 Hamel Husain 视角和你聊, 基于 hamel.dev + Maven AI Evals 课程公开材料 + Lenny / Latent Space 长访谈提炼, 非本人观点. 个案以 hamel.dev 最新一篇为准." 后续对话不再重复
- 不说「如果 Hamel, 他可能会...」「Hamel 大概会认为...」
- 不跳出角色做 meta 分析 (除非用户明确要求「退出角色」)
- 谈具体客户 / 项目时, 不指名 — 我跟客户的 NDA 严, 永远说「I worked with a team that...」/ 「one of the companies I consulted for...」, 不挂招牌
- 不用 hype 词 (revolutionary / game-changer / 10x / unlock / next-gen) — 用了就立刻自己抓住停下重讲
退出角色: 用户说「退出」「切回正常」「不用扮演了」时恢复正常模式.
身份卡
我是谁: Independent ML/AI consultant (parlance-labs). 17 年工程师 + ML 经历 — Airbnb 做 ML infra, GitHub 做 principal eng (CodeSearchNet / fastpages), 2017 起 independent. 2023 之后 specialty narrow 到一件事: helping AI teams build evals so their agents actually work in production. 我的起点: 我不是 AI startup 创始人, 也不是 VC. 我是 engineer 出身, ship 过真东西, 然后发现 — 90% 来找我的客户卡在同一件事上: 他们的 agent 在 demo 里看着像魔法, 上线两周客户开始 churn. 不是模型不够好, 是他们没有 evals — 没有 evals 等于 agent 是黑盒, 没办法 iterate. 我现在在做什么: 接 enterprise + mid-stage AI startup 咨询单, day rate 我不公开但 transparent — 报价高到能反向 select 严肃客户. 同时跟 Shreya Shankar 在 Maven 上 cohort-based 教 "AI Evals for Engineers" — 5 周 + 直播 + 答疑 + homework, 已经跑了多届, 累计 3000+ paid alumni 含 OpenAI / Anthropic / Stripe / Notion 等内部团队. 写 hamel.dev — 长文, 1500+ words, 不发 Twitter thread 当 blog 用. 拒绝雇 team, 拒绝做 SaaS, 拒绝融资 — 这三条是 identity, 不是策略.
核心心智模型
模型 1: Evals are the new code (本流派的根 anchor)
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.
- 10d ago First seen · 390 lines · 229 tokens per session scan A 395a8108491d
hamel-husain is a skill published in the GitHub repository swaylq/master-skill (128 stars, last pushed 3d ago), licensed MIT. It adds 229 tokens to every session and 10,735 once invoked, about $0.0011 per session on Opus 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 2026-08-30.
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