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 dhicoc/wuyun-liuqi-skills --skill emotion-organ-proxygit clone --depth 1 https://github.com/dhicoc/wuyun-liuqi-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/dhicoc/wuyun-liuqi-skills/emotion-organ-proxy)<a href="https://agentmods.dev/skills/dhicoc/wuyun-liuqi-skills/emotion-organ-proxy"><img src="https://agentmods.dev/badge/skills/dhicoc/wuyun-liuqi-skills/emotion-organ-proxy/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/dhicoc/wuyun-liuqi-skills/emotion-organ-proxy"><img src="https://agentmods.dev/badge/skills/dhicoc/wuyun-liuqi-skills/emotion-organ-proxy.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 | $0.00134 | $0.02558 |
| Opus 5 | $0.00067 | $0.01279 |
| Sonnet 5 | $0.00027 | $0.00512 |
| Haiku 4.5 | $0.00013 | $0.00256 |
Grade A, and why
emotion-organ-proxy 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.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
情志脏腑关联模型 (Emotion-Organ Proxy)
R — 原文 (Reading)
怒伤肝,悲胜怒;喜伤心,恐胜喜;思伤脾,怒胜思;忧伤肺,喜胜忧;恐伤肾,思胜恐。百病生于气也,怒则气上,喜则气缓,悲则气消,恐则气下,寒则气收,炅则气泄,惊则气乱,劳则气耗,思则气结。
— 《素问·阴阳应象大论篇第五》/《素问·举痛论篇第三十九》
I — 方法论骨架 (Interpretation)
情绪不是单纯的心理现象,而是有明确生理方向的气机运动。每种核心情绪对应一个脏腑, 且有特定的气机方向:怒→气上(肝)、恐→气下(肾)、喜→气缓(心)、悲→气消(肺)、 思→气结(脾)、惊→气乱。长期处于某种情绪,对应的脏腑就会因气机偏颇而受损。 反过来,利用五行相克的原理,可以用一种情绪来制约另一种情绪——悲胜怒(金克木)、 恐胜喜(水克火)、怒胜思(木克土)、喜胜忧(火克金)、思胜恐(土克水), 这就是"以情胜情"的调节术。但这不是简单的"用开心对抗悲伤", 而是有一套严格的情绪→脏腑→气机→调节策略的分析链。
A1 — 书中的应用 (Past Application)
案例 1: 怒则气上的生理路径
- 问题: 愤怒为什么会导致具体身体症状
- 方法论的使用: 举痛论详述:怒则气逆,甚则呕血及飧泄。气机向上冲逆,上则呕血(气迫血上溢),下则飧泄(肝木乘脾土)
- 结论: 一次暴怒就可能导致气血上逆(头痛面红)和消化紊乱的双重症状
- 结果: 形成了"情绪→气机方向→具体症状"的完整推理链
案例 2: 恐则气下的生理路径
- 问题: 恐惧为什么会导致下肢和泌尿问题
- 方法论的使用: 恐则精却,却则上焦闭,闭则气还,还则下焦胀。恐惧使精气下退,上焦不通,气机全部下坠,导致下腹胀满、二便失常
- 结论: 恐惧的气机方向是"向下向内收缩",对应肾的封藏功能过度
- 结果: 解释了极度恐惧时"腿软""失禁"等现象的气机机制
案例 3: 以情胜情的治疗术
- 问题: 如何不用药物调节情绪过激造成的脏腑损伤
- 方法论的使用: 阴阳应象大论给出五组"以情胜情"关系。例如:一个人过度愤怒伤肝,可以用悲来制约(悲胜怒,金克木);一个人过度思虑伤脾,可以激发怒来破除(怒胜思,木克土)
- 结论: 情绪本身既是致病因素,也是治疗工具,关键是利用五行相克来制约
- 结果: 形成了一套不依赖药物的纯情绪调节疗法
A2 — 触发场景 (Future Trigger) ★
用户会在什么情境下需要这个 skill?
- 长期处于某种强烈情绪中(持续愤怒/焦虑/悲伤/恐惧),开始出现身体症状
- 出现不明原因的身体不适,怀疑可能与近期情绪状态有关
- 想了解特定情绪会对身体造成什么长期影响,以便自我觉察
- 需要用一种情绪来化解另一种过激情绪(如用运动发泄愤怒来破除过度思虑)
语言信号 (用户的话里出现这些就应激活)
- "我最近一直在生气/焦虑,感觉身体也出问题了"
- "情绪不好的时候身体也跟着不舒服"
- "为什么我一生气就头疼/胃疼"
- "有没有办法不靠药物调节情绪"
- "长期焦虑/悲伤对身体有什么影响"
- "我控制不住自己的情绪,怎么办"
与相邻 skill 的区分
- 与
observation-inference的区别: 以外测内推理法是从外部可观察信号(面色/脉象/声音)推断内部状态,情志脏腑模型是从情绪推断脏腑状态。两者都是推断内部的方法,但信号来源不同——前者是物理信号,后者是情绪信号。 - 与
seasonal-regimen的区别: 四时调养中的情志调节是按季节方向调整(春天生发、冬天收敛),情志脏腑模型是按具体情绪类型分析脏腑影响并选择调节策略。前者是时间驱动的,后者是情绪驱动的。
E — 可执行步骤 (Execution)
当 skill 被激活后, agent 应按以下步骤执行:
-
识别用户当前的主导情绪
- 完成标准: 已从用户描述中识别出当前最强烈、最持续的情绪类型(怒/喜/悲/恐/思/惊中的一种或几种)
-
映射到对应脏腑和气机方向
- 完成标准: 已将主导情绪映射到对应脏腑(怒→肝、喜→心、悲→肺、恐→肾、思→脾)和气机方向(上/下/缓/消/结/乱),并指出可能的身体症状
-
选择调节策略(疏导或以情胜情)
- 完成标准: 已根据情绪类型给出两种调节路径:
- 疏导:让该情绪自然流动而非压抑(如允许悲伤哭泣而非强行振作)
- 以情胜情:利用五行相克关系选择制约情绪(如悲胜怒、恐胜喜),并说明如何安全地引入制约情绪
- 判停条件:若用户情绪状态极度不稳定,建议优先寻求专业心理帮助,不建议自行使用以情胜情
- 完成标准: 已根据情绪类型给出两种调节路径:
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 · 140 lines · 134 tokens per session scan A f2f8f0734bf0
emotion-organ-proxy is a skill published in the GitHub repository dhicoc/wuyun-liuqi-skills (42 stars, last pushed 27d ago), licensed MIT. It adds 134 tokens to every session and 2,558 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 2026-08-30.
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