合理情绪疗法（ABC）结构化咨询框架
基于ABC理论的标准化CBT咨询流程，用于识别诱发事件（A）、情绪行为后果（C）与中间不合理信念（B），并系统修正认知偏差。适用于以非理性信念为核心的情绪适应问题。
npx skills add ECNU-ICALK/AutoSkill --skill 合理情绪疗法（ABC）结构化咨询框架 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 合理情绪疗法（ABC）结构化咨询框架 基于ABC理论的标准化CBT咨询流程，用于识别诱发事件（A）、情绪行为后果（C）与中间不合理信念（B），并系统修正认知偏差。适用于以非理性信念为核心的情绪适应问题。 ## Prompt 1. 与求助者共同确认具体情绪/behavior困扰（C）；2. 追溯对应诱发事件（A），确保其为可观察、可验证的客观事实；3. 引导识别伴随A→C过程中的自动思维与核心信念（B），聚焦非理性特征（如绝对化、过度概括、灾难化）；4. 协助检验B的真实性与功能性，生成替代性合理信念（D）；5. 共同制定行为验证计划（E）以巩固新认知。全程保持结构化标注与共识确认。 ## Objective 建立可复用的CBT宏观干预路径 ## Applicable Signals - 表达‘我必须…’‘别人应该…’‘这太糟糕了’等绝对化语言 - 情绪反应强度显著超过事件客观严重性 - 同一类事件反复引发相似强烈负性反应 ## Contraindications - 危机状态需立即安全干预 - 求助者无现实检验能力或严重精神病性症状 - 主要问题为创伤闪回或解离性障碍 ## Intervention Moves - Socratic questioning to examine belief evidence - Behavioral experiment design for belief testing - Collaborative identification of cognitive distortions ## Workflow Steps - Step 1: Jointly define and document C (emotion/behavior outcome) - Step 2: Identify and anchor A (concrete, observable activating event) - Step 3: Elicit and label B (irrational belief with distortion type) - Step 4: Challenge B via evidence review and generate D (rational alternative) - Step 5: Co-create E (behavioral action to test/reinforce D) ## Constraints - A must be factually verifiable, not interpreted - B must be stated in first-person, present-tense language - All D statements must be empirica
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What does the 合理情绪疗法（ABC）结构化咨询框架 skill do?
基于ABC理论的标准化CBT咨询流程，用于识别诱发事件（A）、情绪行为后果（C）与中间不合理信念（B），并系统修正认知偏差。适用于以非理性信念为核心的情绪适应问题。
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill 合理情绪疗法（ABC）结构化咨询框架 --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.