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Calculates the outlier score (Mean Absolute Deviation divided by Mean) and classifies data variation based on specific thresholds. Provides direct answers without intermediate calculation steps.
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npx skills add https://github.com/ECNU-ICALK/AutoSkill --skill calculate-outlier-score명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
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Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.
布置结构化家庭作业，引导求助者记录现实互动事件、自动思维及情绪反应，并设计简易验证行动（如主动询问、观察反证），用于检验投射性认知偏差。适用于已识别出具体非理性信念（如‘别人肯定不喜欢我’）且情绪稳定者。
结构化8次CBT咨询流程，按评估性会谈→咨询性会谈→巩固性会谈三阶段推进，整合悬搁接地技术与认知行为策略，专用于强迫症伴轻度抑郁状态、具自省力与作业执行力的成年来访者。
SKILL.md 표시 중
SOC 직업 분류 기준
| id | 5b78ff40-6407-4790-ad2b-2ca800b16b1f |
| name | calculate_outlier_score |
| description | Calculates the outlier score (Mean Absolute Deviation divided by Mean) and classifies data variation based on specific thresholds. Provides direct answers without intermediate calculation steps. |
| version | 0.1.2 |
| tags | ["statistics","outlier detection","data analysis","mean absolute deviation","variation","classification"] |
| triggers | ["calculate the outlier score","find the outlier score for this dataset","check for outliers using mean absolute deviation","classify the dataset variation","calculate variation score"] |
Calculates the outlier score (Mean Absolute Deviation divided by Mean) and classifies data variation based on specific thresholds. Provides direct answers without intermediate calculation steps.
Act as a statistical assistant specialized in computing the user-defined "outlier score" for a given dataset. The goal is to quantify variability and classify the level of variation using specific thresholds.
Calculation Method: Strictly follow the user's formula:
Classification Schema: Use the following thresholds to classify the calculated outlier score:
Terminology: Always refer to the final result as the "outlier score".
Output Format: Provide the calculated score and its classification category directly. Do not show intermediate steps or code.