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 huo-yue-zai-yuangit 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/huo-yue-zai-yuan)<a href="https://agentmods.dev/skills/ace3000chao/book2startup/huo-yue-zai-yuan"><img src="https://agentmods.dev/badge/skills/ace3000chao/book2startup/huo-yue-zai-yuan/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/huo-yue-zai-yuan"><img src="https://agentmods.dev/badge/skills/ace3000chao/book2startup/huo-yue-zai-yuan.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 | $0.00200 | $0.02110 |
| Opus 5 | $0.00100 | $0.01055 |
| Sonnet 5 | $0.00040 | $0.00422 |
| Haiku 4.5 | $0.00020 | $0.00211 |
Grade A, and why
huo-yue-zai-yuan 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 13d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
或跃在渊,进无咎
R — 原文 (Reading)
"或跃在渊,无咎。" "知至至之,可与言几也。知终终之,可与存义也。" — 《易经》乾卦·九四
I — 方法论骨架 (Interpretation)
"或跃在渊"描述的是龙在深渊中蓄势、伺机跃起的状态——不是盲目冲撞,也不是永远潜伏,而是在准确判断时机后的一跃。
"知至至之,可与言几":知道目标在哪里、知道何时到达那个点,才能谈论时机。这句话道出了本skill的核心——对"临界点"的感知和把握。
应用到创业实践中:
- 渊的理解:深渊不是失败,而是蓄势。团队能力、资源积累、市场条件都在深渊中等待
- 跃的准备:起跳前需要确认三件事——内在能力是否到位、外在时机是否成熟、失败退路是否清晰
- 进无咎:只要是经过审慎判断后的跃,失败了也不会有咎——因为咎不在行动本身,而在于盲目或犹豫
- 知至至之:知道你要到达的位置,知道何时到达那里,这是能不能谈"时机"的前提
本质是在"蓄势"与"起跳"之间找到精准节奏,不早不晚,恰到好处。
A1 — 书中的应用 (Past Application)
案例1: 文王克崇
- 问题: 周文王面对商朝强权,在时机未成熟时如何在韬光养晦中等待,同时为最终伐纣做准备
- 方法论的使用: 文王被困羑里七年,在"渊"中潜心演易、积蓄力量、等待时机;他知道自己的"跃"要等到商朝内部彻底腐化和周族实力足够强大两个条件同时满足
- 结论: 文王以"在渊"的姿态完成力量积累,等到"跃"的窗口打开,一举奠定周朝根基
- 结果: 牧野之战时机成熟,武王完成文王未竟之业,周朝建立
案例2: 华为技术突破前的静默期
- 问题: 华为在通信设备领域从追赶者到领先者的过程中,如何判断"跃"的时机
- 方法论的使用: 任正非提出"不在非战略机会点上消耗战略竞争力量",华为在多个技术路线上长期蓄势(渊),直到某个技术代际更替的窗口打开(跃)
- 结论: 华为的跳跃不是追赶期的冒进,而是在充分蓄势后的精准出击
- 结果: 华为在5G时代成为全球领导者,而非在2G/3G时代过度消耗
A2 — 触发场景 (Future Trigger) ★
用户会在什么情境下需要这个 skill?
- 创业者在机会面前犹豫——项目已准备就绪,但不确定"现在是否是时候";或已多次推迟行动
- 团队面临重大战略选择:是继续深耕现有业务(渊),还是进入新市场/推出新产品(跃)
- 外部投资者、合伙人、员工都在催促行动,但创业者内心感到时机可能未到
语言信号
- "这个机会很好,但我们还没准备好"
- "再等等,等XXX就绪了"
- "现在上还是半年后上?"
- "大家都说可以动了,我总觉得还差点什么"
- "如果失败了怎么办,但不进也不行"
与相邻 skill 的区分
- 与 ce01(亢龙有悔)的区别: ce01是"已经跃得太高、过于亢进而失败";本skill是"如何判断该不该跃",属于起跳前的决策框架;两者方向相反
- 与 p13(穷则变)的区别: p13强调"穷则必须变",本skill强调"在渊蓄势才能跃",不是被迫应变而是主动等待时机
E — 可执行步骤 (Execution)
-
盘点"渊"的深度——我们真的准备好了吗
- 完成标准: 列出"内在准备度"清单:核心能力(1-10分)、资源储备(1-10分)、团队状态(1-10分),总分≥21分进入下一步
- 判停条件: 若总分<18分,明确告知"渊还不够深,现在跳跃风险过高"
-
识别"跃"的窗口——时机真的到了吗
- 完成标准: 列出"外在时机"条件:市场窗口(打开/即将打开/关闭)、竞争对手动向(是否有空窗)、政策环境(有利/中性/不利),至少2项有利
- 判停条件: 若外在条件均不利,继续蓄势,不执行跳跃
-
确认退路——失败了怎么办
- 完成标准: 制定"最坏情况预案":最坏结果是什么?这个结果是否可以承受?有没有保底线?
- 判停条件: 若最坏结果无法承受,暂停跳跃,重新评估规模或方式
-
执行跳跃——进无咎
- 完成标准: 确定"行动触发点"(具体的、可观察的信号),一旦触发立即执行,不犹豫
- 判停条件: 若触发后犹豫超过72小时,重新进入步骤1评估
B — 边界 (Boundary) ★
不要在以下情况使用此 skill
- 已经在坠落中——这属于ce01亢龙有悔的范畴,不是"在渊蓄势"而是"已经跃了并失败",此时需要的是救险而不是判断时机
- 极小规模的试水(小额测试、新功能灰度发布)——这些不值得动用完整的时机判断框架,轻量决策即可
- 机会窗口极短(<72小时)——时间窗口太短时,分析框架反而耽误行动,此时凭直觉快速决策
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.
- 13d ago First seen · 132 lines · 200 tokens per session scan A 2feaadb14488
huo-yue-zai-yuan is a skill published in the GitHub repository ace3000chao/book2startup (80 stars, last pushed 4mo ago), licensed MIT. It adds 200 tokens to every session and 2,110 once invoked, about $0.0010 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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