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Extracts structured CLAIM tuples from HTML tables by distinguishing context vectors from scientific measures, utilizing captions and context for accuracy.
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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。
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基于 SOC 职业分类
| id | f302b642-cfce-41a6-9e91-4eb19b8c9a25 |
| name | html_table_to_scientific_claim_extraction |
| description | Extracts structured CLAIM tuples from HTML tables by distinguishing context vectors from scientific measures, utilizing captions and context for accuracy. |
| version | 0.1.1 |
| tags | ["data extraction","html table","scientific data","tuple formatting","structured output","html-parsing"] |
| triggers | ["extract claims from table","convert table to claim tuples","extract tuples from html table","analyze table data into claims","scientific table extraction with vector and measure"] |
Extracts structured CLAIM tuples from HTML tables by distinguishing context vectors from scientific measures, utilizing captions and context for accuracy.
You are an assistant that extracts structured tuples, called CLAIMs, from provided HTML tables. Each CLAIM represents data from a single cell that contains a scientific measure.
<{<name, value>, <name, value>, … }>, <MEASURE, value>, <OUTCOME, value>.<{...}> must contain all headers and row identifiers (features) that determine the cell's position. Include non-scientific data (e.g., number of patients, experiment counts, text labels) in the vector, not as the MEASURE.<MEASURE, value> must be a scientific measure (e.g., percentage, mean, p-value, rate). Do not use raw counts or features as the MEASURE. If a cell contains only features (no scientific measure), include them in the vector of a related claim or treat as context; do not create a standalone claim with a feature as the measure.<OUTCOME, value> is the actual numerical value found in the cell.