What is personalize-by-constitution?

A planning framework that adjusts a solution to each person's situation instead of applying one fixed version to everyone. It considers differences such as ability, age, preferences, and other relevant conditions before changing the plan's settings.

Use it to tailor plans, tune their intensity or other parameters, and assign work according to team members' abilities and styles. It is useful when a standard approach produces uneven results.

It helps explain why a method may work for one person but not another. The framework emphasizes observing the individual first and then changing the approach to fit.

personalize-by-constitution — Skill for Claude Code by dhicoc

Install

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.

Any agent

npx skills add dhicoc/wuyun-liuqi-skills --skill personalize-by-constitution

Clone the repo

git clone --depth 1 https://github.com/dhicoc/wuyun-liuqi-skills

Made for: Claude Code.

Or install wuyun-liuqi-skills, the plugin that ships this one along with the rest of its 38 skills.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/dhicoc/wuyun-liuqi-skills/personalize-by-constitution/github.svg)](https://agentmods.dev/skills/dhicoc/wuyun-liuqi-skills/personalize-by-constitution)

Your own site

<a href="https://agentmods.dev/skills/dhicoc/wuyun-liuqi-skills/personalize-by-constitution"><img src="https://agentmods.dev/badge/skills/dhicoc/wuyun-liuqi-skills/personalize-by-constitution/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/dhicoc/wuyun-liuqi-skills/personalize-by-constitution"><img src="https://agentmods.dev/badge/skills/dhicoc/wuyun-liuqi-skills/personalize-by-constitution.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,441 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00073	$0.01441
Opus 5	$0.00036	$0.00720
Sonnet 5	$0.00015	$0.00288
Haiku 4.5	$0.00007	$0.00144

Measured 12d ago against content hash fd66f1413dc2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

personalize-by-constitution 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.

scripts/lib/neijing_snapshot/lingshu/personalize-by-constitution/SKILL.md · 109 lines

What it actually says

因人施术原则

R — 原文 (Reading)

年质壮大, 血气充盈, 肤革坚固……深而留之。瘦人者, 皮薄色少, 肉廉廉然, 薄唇轻言……浅而疾之。婴儿者, 其肉脆, 血少气弱……以豪刺, 浅刺而疾拔针。古之善用针艾者, 视人五态乃治之。

— 黄帝/岐伯, 逆顺肥瘦第三十八、通天第七十二

I — 方法论骨架 (Interpretation)

因人施术是一个根据个体差异调整方案参数的决策框架。

识别差异维度: 哪些个体差异会影响方案效果? 灵枢关注: 体质(肥/瘦/壮/弱)、年龄(老/壮/少/婴)、人格(五态)、社会身份(布衣/王公)。不同维度对应不同的参数调整。
参数因人而异: 同样的方案框架, 关键参数(深度、速度、强度、频率)必须因人而异。肥人深留、瘦人浅疾、婴儿最浅最快——方向相同但参数不同。
匹配而非标准化: "因适而为之真"——最匹配个体特点的方案才是最好的, 而不是"标准方案"最好。
先观察后调整: 必须先通过"司外揣内"识别个体特点, 然后据此调整, 不能凭主观臆断。

A1 — 书中的应用 (Past Application)

案例 1: 肥瘦壮弱的参数差异

问题: 同样的针刺, 不同体质需要什么不同的参数?
方法论的使用: 肥人(血浊气涩)→深而留之多益其数; 瘦人(血清气滑)→浅而疾之; 常人→无失常数; 壮士(重)→深而留; 壮士(劲)→浅而疾; 婴儿→浅而疾拔, 日再可。
结论: 六种体质, 六套参数。参数差异来自气血的"滑/涩"和"强/弱"。
结果: 每种体质都获得了最匹配的方案, 避免了"一刀切"的无效或伤害。

案例 2: 王公与布衣的不同

问题: 社会阶层不同的患者, 刺法是否不同?
方法论的使用: "膏梁菽藿之味, 何可同也?"王公大人身体柔脆、气血慓悍滑利, 需要"微以徐之"。布衣匹夫血气沉涩, 需要"深以留之"。
结论: 生活方式(饮食/运动)塑造体质, 体质决定方案参数。
结果: 不以"相同方案"为公平, 而以"最匹配方案"为公平。

A2 — 触发场景 (Future Trigger) ★

标准化方案失效: 同样的方案对A有效对B无效, 需要因人而异。
参数调整: 方案框架正确但效果不理想, 需要微调参数。
团队管理: 需要根据不同成员的能力和风格分配不同任务。

语言信号

"同样的方法为什么对别人有效对我不行"
"一刀切方案行不通"
"不同的人需要不同的对待"
"怎么根据实际情况调整"

E — 可执行步骤 (Execution)

识别影响效果的差异维度
- 列出可能影响方案效果的个体特征(能力/经验/偏好/资源)。
- 完成标准: 至少识别出2个关键差异维度。
建立差异-参数映射
- 每个差异维度如何影响方案的关键参数(深度/速度/强度/频率)?
- 完成标准: 明确的映射表, 差异→参数调整方向。
定制方案
- 根据映射关系, 调整方案参数, 生成定制化版本。
- 完成标准: 至少1个关键参数被调整, 并说明调整理由。

B — 边界 (Boundary) ★

不要在以下情况使用

标准化优先: 有些场景(如安全规程)确实需要标准化, 个性化可能导致安全风险。

失败模式

过度个性化: 每个人都不同不等于每个人都需要完全不同的方案, 关键是识别影响效果的差异维度。
刻板印象: 把外貌/身份直接等同于能力, 而不是通过实际观察判断。

审计信息

验证通过: V1 ✓ / V2 ✓ / V3 ✓
测试通过率: {{%}} (详见 test-prompts.json)
蒸馏时间: {{DATE}}

Changes

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 · 109 lines · 73 tokens per session scan A fd66f1413dc2

Subscribe to this mod's changes

personalize-by-constitution is a skill published in the GitHub repository dhicoc/wuyun-liuqi-skills (42 stars, last pushed 27d ago), licensed MIT. It adds 73 tokens to every session and 1,441 once invoked, about $0.0004 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.

Planning 公众号

personalize-by-constitution