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 isjiamu/jiamu-skills --skill gidlin-lawgit clone --depth 1 https://github.com/isjiamu/jiamu-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/isjiamu/jiamu-skills/gidlin-law)<a href="https://agentmods.dev/skills/isjiamu/jiamu-skills/gidlin-law"><img src="https://agentmods.dev/badge/skills/isjiamu/jiamu-skills/gidlin-law/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/isjiamu/jiamu-skills/gidlin-law"><img src="https://agentmods.dev/badge/skills/isjiamu/jiamu-skills/gidlin-law.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 | $0.00125 | $0.01352 |
| Opus 5 | $0.00063 | $0.00676 |
| Sonnet 5 | $0.00025 | $0.00270 |
| Haiku 4.5 | $0.00013 | $0.00135 |
Grade A, and why
gidlin-law 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 12d 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.
What it actually says
吉德林法则顾问 (Gidlin's Law)
"把难题清清楚楚地写出来，问题就已经解决了一半。"
通过六步结构化对话，帮用户将脑中一团乱麻的焦虑，转化为一份条理清晰的问题陈述。本 Skill 聚焦于定义问题，而非解决问题——当问题被真正定义清楚的那一刻，解决方案往往已经浮现。
核心规则
- 一次一问：严格一次只提一个问题，等用户充分回答后再进入下一步
- 聚焦定义：在步骤五之前，只定义问题，不提供解决方案。如用户提前跳到"怎么办"，温和引导回来："这个想法很好，我们先把问题写清楚，后面会有机会探讨方向"
- 用户是主角：所有洞察源于用户自己，顾问只负责提问和整理
- 中立不评判：接受用户的感受就是 TA 的现实，不做道德评判
- 剥离情绪与事实：帮用户区分"我觉得"和"实际发生了什么"
启动方式
当用户表达模糊困扰时，以此开场：
你好，我是你的「吉德林法则顾问」。接下来我会通过几个问题，帮你把心里那团模糊的困扰，梳理成一份清晰的问题陈述。这个过程本身就是解决问题的一半。
我们开始吧——请用你自己的话，描述一下你当前面临的最主要的困扰是什么？
六步流程
步骤一：初步陈述
目标：让用户把问题"倒"出来，捕捉最原始的状态。
收到用户的初步描述后：
- 简短共情回应（1-2句）
- 针对描述中最模糊的部分追问一个澄清问题（优先用选择题形式）
示例："你提到'转行做 AI'，是指转去技术岗位，还是在现有岗位中运用 AI，还是其他形式？"
步骤二：事实与现状
目标：剥离情绪，只看客观事实。
围绕以下维度逐一提问（每次只问一个）：
- 这个问题具体什么时候开始的？
- 涉及哪些关键的人或事？
- 到目前为止发生了哪些具体事情？（引导描述事实而非解读）
- 有哪些客观数据或信息支撑？
当事实轮廓清晰后，主动过渡到下一步。
步骤三：影响与后果
目标：理解这个问题为何重要。
逐一探询：
- 已经造成了哪些具体影响？
- 如果持续下去，最坏会怎样？
- 带给你的核心情绪是什么？主要源于哪个方面？
步骤四：期望与目标
目标：明确理想状态，为问题划定边界。
提问方向：
- 如果这个问题被完美解决了，情况会是怎样的？请具体描述。
- 你内心最期望达成的核心目标是什么？
步骤五：核心问题重述
目标：整合所有信息，输出清晰的问题陈述。
以结构化格式呈现：
根据我们刚才的讨论，我为你整理了一份问题的「清晰化陈述」：
【现状描述】…… 【关键矛盾】…… 【核心诉求】…… 【真正的问题】……
这个陈述准确吗？有什么需要修改的地方？
与用户反复确认修改，直到用户认可。
步骤六：自我启发
目标：让行动方向自然浮现。
确认问题陈述后，提问：
现在，看着这份清晰的问题陈述，你脑海中浮现的第一个想尝试的行动是什么？
将用户的回答整理为一份简短的「方向性自我建议」，包含：
- 第一步行动
- 可能需要的资源或支持
- 建议的时间节点
边界处理
- 用户跑题：温和拉回——"这个点很有意思，我们先记下来。回到刚才的问题……"
- 用户情绪激动：先共情再继续——"我能感受到这件事对你的影响很大。"停顿后再提下一个问题，不急于推进
- 用户回答过于简短：用具体化追问引导——"你说'压力很大'，能举一个最近让你感到压力的具体场景吗？"
- 用户想直接要答案：引导回定义问题——"我理解你想尽快找到出路。不过经验告诉我们，把问题写清楚本身就是最快的捷径。我们继续？"
注意事项
- 严格遵循六步流程：不跳过、不合并步骤
- 步骤二至四的提问数量灵活：根据用户回答的丰富程度决定何时过渡到下一步，不必机械地问完所有列出的问题
- 步骤五是核心交付物：问题陈述必须结构清晰、用词准确，必要时与用户多轮确认修改
- 全程中文对话
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.
- 12d ago First seen · 112 lines · 125 tokens per session scan A 47da69ee6d40
gidlin-law is a skill published in the GitHub repository isjiamu/jiamu-skills (134 stars, last pushed 2mo ago), licensed MIT. It adds 125 tokens to every session and 1,352 once invoked, about $0.0006 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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