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 ace3000chao/book2startup --skill f30git clone --depth 1 https://github.com/ace3000chao/book2startupWrote 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/ace3000chao/book2startup/f30)<a href="https://agentmods.dev/skills/ace3000chao/book2startup/f30"><img src="https://agentmods.dev/badge/skills/ace3000chao/book2startup/f30/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/ace3000chao/book2startup/f30"><img src="https://agentmods.dev/badge/skills/ace3000chao/book2startup/f30.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.02095 |
| Opus 5 | $0.00074 | $0.01047 |
| Sonnet 5 | $0.00030 | $0.00419 |
| Haiku 4.5 | $0.00015 | $0.00210 |
Grade A, and why
f30-saint-commoner-integrated 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 9d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
圣凡一体观
R — 原文 (Reading)
"标节义者，必以节义受谤；标道学者，常因道学招尤。故君子不近恶事，亦不立善名，只浑然和气，才是居身之珍。"
— 洪应明, 浑然和气 处事珍宝
I — 方法论骨架 (Interpretation)
这是不走极端的中道处世框架，针对的是"道德洁癖"和"虚伪善名"两种极端：
两个极端的危险：
-
标榜节义（道德洁癖）：越标榜自己的道德，反而越容易因道德受诽谤。因为一旦有了"我是好人"的人设，任何小失误都会被放大。
-
标榜道学（虚伪善名）：越强调自己的道学修养，越容易招来非议。因为"强调道学"本身就已经不道学了。
正确的态度：不近恶事（不做坏事）+ 不立善名（不追求"好人"标签）= 浑然和气
核心逻辑：真正的高手，不做好事以证明自己是好人，也不做坏事以迎合世俗。他们只是自然地存在着，不走两个极端。这就是"圣凡一体"——既不圣洁到脱离世俗，也不凡俗到失去自我。
A1 — 书中的应用 (Past Application)
案例 1: 项羽和李斯败亡的对比
- 问题: 项羽拥有极高天赋和贵族身份，却因极端性格而败亡
- 方法论的使用: 项羽"富贵而反忌刻"——有富贵却刻薄待人，不走中道；李斯聪明却"以物役我"，不知收敛。两者都走了极端
- 结论: 极端的性格（不论是极善还是极恶）都会导向失败
- 结果: 项羽乌江自刎，李斯被腰斩；反观刘邦以宽厚待人而成帝业
案例 2: 包拯和海瑞的平衡
- 问题: 包拯和海瑞以刚正著称，但刚正到极点会有问题
- 方法论的使用: 两人虽然严格执法，但并不是为了"立善名"，而是自然地做该做的事；他们也懂得在必要时妥协
- 结论: 刚正本身没问题，但若"标榜刚正"就会变成"偏激"
- 结果: 包拯、海瑞千古流芳，但不是以"完人"形象，而是以"和而不同"的方式被后人记住
案例 3: 曾国藩的修身之道
- 问题: 曾国藩位极人臣，功高震主，如何保全自身
- 方法论的使用: 他深知"标节义者必受谤"的道理，在功成名就后主动裁军，不立功名，以"浑然和气"自处
- 结论: 不立善名，才能保全自己
- 结果: 曾国藩功成身退，善终于世
A2 — 触发场景 (Future Trigger) ★
用户会在什么情境下需要这个 skill?
- 道德拉扯：在"坚持原则"和"灵活变通"之间纠结，不确定什么时候该坚持、什么时候该妥协
- 形象焦虑：担心自己"太清高"被人疏远，或者担心"太随和"被人利用
- 标签执念：执着于"我是好人/有原则的人/不好说话的人"等标签，被标签所累
- 人际平衡困惑：不知道对不同的人应该用什么态度——对上级要谄媚吗？对下级要严厉吗？
语言信号 (用户的话里出现这些就应激活)
- "我不知道该坚持原则还是随大流"
- "我怕自己太清高了"
- "做好人会吃亏怎么办"
- "既要做好人又要不吃亏，可能吗"
- "我是不是太较真了"
- "我总觉得要保持形象，不能……"
- "别人都这么做，我要不要也……"（跟随vs坚持的拉扯）
- "我不知道该怎么拿捏这个度"
与相邻 skill 的区分
- 与
f24 不为法缠不为人缠框架的区别：f24强调"不被任何规范束缚"，本框架强调"不刻意立善名也不刻意做恶"——两者都走中道，但f24更激进（彻底不缠），本框架更日常（不标榜） - 与
f04 中和处世决策框架的区别：f04关注性格偏激（躁/刻/执），本框架关注道德形象（不立善名）
E — 可执行步骤 (Execution)
当 skill 被激活后, agent 应按以下步骤执行:
-
识别"标签执念"
- 完成标准: 用户问自己："我是不是执着于'我是XX的人'这个标签？"——找到自己最执着的一个标签
-
执行"去标签测试"
- 完成标准: 用户想象：如果我明天不是"XX的人"了，我还是我吗？——如果答案是"是"，则标签是工具；如果答案是"否"，则标签是牢笼
- 判停条件: 若用户处于需要明确道德立场的场合（如商业谈判/法律事务），先去标签化可能会导致失去立场，此时需结合f09判断
-
找到"浑然和气"的基准
- 完成标准: 用户回答：什么行为是"不刻意做善事，但也不做恶事"的具体表现？（例：不给别人贴标签、不主动炫耀自己的付出、不因为"我是好人"而委屈自己）
What ships with it
1 file 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.
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.
- 9d ago First seen · 139 lines · 148 tokens per session scan A f7e92b019c94
f30-saint-commoner-integrated is a skill published in the GitHub repository ace3000chao/book2startup (80 stars, last pushed 4mo ago), licensed MIT. It adds 148 tokens to every session and 2,095 once invoked, about $0.0007 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 2026-09-03.
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