context-adaptation

context-adaptation is a skill for Claude Code from dhicoc/wuyun-liuqi-skills. It costs 94 tokens per session (2,263 once invoked), scanned A, original, MIT.

A method for adapting an existing solution to a different place, market, culture, or operating environment. It starts by examining local conditions before deciding what to change or combine.

In plain words
What is it for?
Use it when moving a proven plan to a new region or situation, deploying it in several different environments, or diagnosing why its results vary from place to place.
Why use it?
It helps explain why a solution that worked in one setting fails in another. It replaces assumptions about a standard environment with adjustments based on local circumstances.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the wuyun-liuqi-skills plugin — 38 skills shipped together

Good fit Use it when moving a proven plan to a new region or situation, deploying it in several different environments, or diagnosing why its results vary from place to place.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dhicoc/wuyun-liuqi-skills/context-adaptation
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 context-adaptation
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.

agentmods badge for context-adaptation

README.md
[![agentmods](https://agentmods.dev/badge/skills/dhicoc/wuyun-liuqi-skills/context-adaptation/github.svg)](https://agentmods.dev/skills/dhicoc/wuyun-liuqi-skills/context-adaptation)
Your own site
<a href="https://agentmods.dev/skills/dhicoc/wuyun-liuqi-skills/context-adaptation"><img src="https://agentmods.dev/badge/skills/dhicoc/wuyun-liuqi-skills/context-adaptation/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.

agentmods 80×15 button for context-adaptation

Your own site · 80×15
<a href="https://agentmods.dev/skills/dhicoc/wuyun-liuqi-skills/context-adaptation"><img src="https://agentmods.dev/badge/skills/dhicoc/wuyun-liuqi-skills/context-adaptation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,263 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00094 $0.02263
Opus 5 $0.00047 $0.01131
Sonnet 5 $0.00019 $0.00453
Haiku 4.5 $0.00009 $0.00226

Measured 12d ago against content hash cee3edea026b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

context-adaptation 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/suwen/context-adaptation/SKILL.md · 142 lines

How it starts

The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Context Adaptation — 因地制宜思维

R — 原文 (Reading)

医之治病也,一病而治各不同,皆愈何也?岐伯对曰:地势使然也。 ……故圣人杂合以治,各得其所宜,故治所以异而病皆愈者,得病之情,知治之大体也。

— 《黄帝内经·素问》,异法方宜论篇第十二


I — 方法论骨架 (Interpretation)

同一个问题在不同环境中会呈现不同的面貌,因此不存在放之四海皆准的单一方案。 素问用五方(东、西、北、南、中)的体质差异和治疗差异来阐明这个原理: 东方人易生痈疡宜砭石,西方人体质刚强宜毒药,北方人脏寒宜灸焫, 南方人挛痹宜微针,中央人痿厥宜导引按蹻——同样的"治病",五个地方五种打法。

关键不在于记住五种方案,而在于掌握"因地"的思维方式: 先分析当前环境的特征(气候、饮食、体质、风俗), 再判断这些特征对方案的影响, 最后选择适配的方案或将多种方案"杂合"使用。

当你的方案在新环境中失效时,问题通常不在方案本身, 而在于你假设了一个"标准环境"——但真实环境永远有地方性。 "杂合以治"进一步提醒:当单一方案不够时,可以组合多个方案, 让每种手段各发挥其适宜的部分,不必执着于唯一解。


A1 — 书中的应用 (Past Application)

案例 1: 五方异治

  • 问题: 同样是治病,为什么东方用砭石、西方用毒药、北方用灸焫、南方用微针、中央用导引按蹻?
  • 方法论的使用: 素问逐一分析五方的地理气候→饮食习俗→体质特征→好发疾病,再给出对应的最佳治法。东方海滨多鱼盐,人多热中痈疡,故宜砭石排脓;北方天寒地冻,人脏寒满病,故宜灸焫温阳。
  • 结论: 治法的差异不是随意的,而是由环境决定的。"地势使然也"——地势不同,方案必须不同。
  • 结果: 五种治法各自在本地区效果最优,但"杂合以治"的高手可以综合运用,"各得其所宜"。

案例 2: 西北与东南的体质差异与治法调整

  • 问题: 同样的病,在西北和东南要用不同的治法。
  • 方法论的使用: 五常政大论指出"西北之气散而寒之,东南之气收而温之,所谓同病异治也"。西北阴精奉上,人体质偏实,需要散邪;东南阳精降下,人体质偏虚,需要固守。
  • 结论: "同病异治"——诊断相同但环境不同,方案必须调整。
  • 结果: 因地施治的患者恢复更快,而照搬方案的疗效不佳。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 方案迁移失效: 用户有一个在A地/A场景/A市场验证成功的方案,迁移到B地/B场景后发现效果大打折扣,需要诊断原因并调整。
  2. 多地并行部署: 用户需要同时在多个不同地区或场景下推行同一个项目/产品/政策,需要因地制宜地设计变体。
  3. 本地化改造: 用户的通用方案需要适配特定文化、气候、法规或用户习惯,不能原样照搬。

语言信号 (用户的话里出现这些就应激活)

  • "为什么在这里管用在那里就不管用了?"
  • "换个地方方案就失效了"
  • "能不能直接复制那个方案过来?"
  • "每个地区的情况不一样"
  • "需要做本地化适配"
  • "一刀切的方案不行"

与相邻 skill 的区分

  • cascade-prediction 的区别: 因地制宜关注的是"同一问题在不同环境下的适配",传变预测关注的是"一个问题如何连锁扩散到其他环节"。前者是空间维度,后者是时间维度。
  • zheng-xie-assessment 的区别: 因地制宜是分析环境特征来调整方案,正邪虚实是评估自身能力vs外部压力来决定补还是泻。前者聚焦环境差异,后者聚焦力量对比。

E — 可执行步骤 (Execution)

当 skill 被激活后, agent 应按以下步骤执行:

  1. 分析当前环境特征

    • 列出目标环境的关键特征: 地理/气候条件、文化/习俗、用户特征、制度/规则约束。
    • 与原方案的假设环境做对比,标记差异点。
    • 完成标准: 产出一份"环境差异清单",至少列出3个显著差异。
  2. 对照方案-环境匹配表

    • 将原方案的每个关键要素逐一与目标环境对照,判断是匹配、冲突还是缺失。
    • 特别关注: 哪些要素在新环境中会失效?哪些要素反而更有价值?哪些新要素需要补充?
    • 完成标准: 对每个关键要素标注"保留/调整/替换/新增"。
    • 判停条件: 若所有要素均匹配无冲突,则说明环境差异不大,可跳到步骤3简化调整。

Read the full file on GitHub · 142 lines

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.

  1. 12d ago First seen · 142 lines · 94 tokens per session scan A cee3edea026b

Subscribe to this mod's changes

context-adaptation is a skill published in the GitHub repository dhicoc/wuyun-liuqi-skills (42 stars, last pushed 27d ago), licensed MIT. It adds 94 tokens to every session and 2,263 once invoked, about $0.0005 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.