Agent skill

虚假担忧情境识别与重构训练

协助来访者区分真实健康风险与由认知偏差生成的虚假担忧情境,通过信念挑战与积极意义赋值,重建对不确定性的适应性解读。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 虚假担忧情境识别与重构训练 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 2 KB
Bundled scripts: none
Version: 0.1.0
Path: SkillBank/DocSkill/心理咨询/Family技能/认知行为疗法/微技能/虚假担忧情境识别与重构训练/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 539
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 虚假担忧情境识别与重构训练 协助来访者区分真实健康风险与由认知偏差生成的虚假担忧情境,通过信念挑战与积极意义赋值,重建对不确定性的适应性解读。 ## Prompt 1. 引导来访者复述当前担忧情境,聚焦具体身体感觉、假设性结果及责任归因;2. 共同核查:是否存在客观医学依据?是否符合概率逻辑(如常见病/罕见病分布)?是否混淆‘可能’与‘必然’?3. 若判定为虚假担忧情境,引导其标注并挑战核心信念(如‘不担忧=不负责’);4. 协助赋义:指出适度担忧的适应性功能(如促准备),同时澄清‘等待’与‘准备’的边界,强调不确定性本身无需被消除。 ## Objective 修正‘担忧=准备=控制’的错误联结,提升不确定性忍受力 ## Applicable Signals - 反复搜索症状信息后仍无法缓解焦虑 - 用‘万一…’句式启动担忧链 - 将模糊身体感觉直接等同于器质病变 ## Contraindications - 担忧基于已确诊的高风险医学状况 - 存在思维奔逸或妄想内容 - 尚未完成基础自动思维识别训练 ## Intervention Moves - 虚假情境三问核查(依据?概率?必然性?) - 中间信念外化命名(如‘责任幻觉’) - 双轨赋义:保留担忧的适应性价值 + 解构其控制幻觉 ## Workflow Steps - 确认当前担忧情境的具体表述(含身体感觉、推演链条、责任判断) - 执行‘虚假担忧三问’:①有无客观医学证据支持?②该结果是否符合流行病学概率?③‘万一’是否等同于‘很可能’? - 若满足至少两项‘否’回答,则共同标注为虚假担忧情境 - 挑战支撑该情境的核心中间信念(例:‘不担忧=失职’→‘有效准备≠持续焦虑’) - 引导赋义:区分‘警觉性准备’与‘消耗性担忧’,明确‘等待期’本身是健康应对的一部分 ## Constraints - 须在来访者已掌握自动思维记录基础上开展 - 避免直接否定担忧感受,始终承认其主观真实性 ## Cautions - 不可跳过证据核查直接进入赋义,否则削弱认知重构可信度 - 当出现躯体化加重时,暂停本训练并回归生理教育或放松技术 ## Output Contract - 来访者能独立标注1个虚假担忧情境,并给出2条以上基于证据的替代性解释 ## Example Therapist Responses ### Example 1 - Client/Input: 我昨天有点喉咙干,现在觉得可能是喉癌,已经查了6个网站,越查越怕,觉得不马上做检查就是对自己不负责任。 - Therapist/Output: 虚假情境标注:‘喉咙干→喉癌’缺乏解剖/流行病学依据(喉癌首发症状极少为单纯干涩);‘不立即检查=不负责任’混淆了合理筛查与过度反应。替代解释:①喉咙干更常见于环境干燥或轻度病毒感染;②规范体检周期内无报警症状

What's inside
Steps it walks through
  1. Prompt
  2. Objective
  3. Applicable Signals
  4. Contraindications
  5. Intervention Moves
  6. Workflow Steps
  7. Constraints
  8. Cautions
  9. Output Contract
  10. Example Therapist Responses
  11. Example 1
  12. Files
  13. Triggers
  14. Examples
Ships with 2 files
  • references/evidence.md
  • references/evidence_manifest.json
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About this skill
What does the 虚假担忧情境识别与重构训练 skill do?

协助来访者区分真实健康风险与由认知偏差生成的虚假担忧情境,通过信念挑战与积极意义赋值,重建对不确定性的适应性解读。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 虚假担忧情境识别与重构训练 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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