yogsoth-ai/de-anthropocentric-research-engine

categorize-evidence

Cluster an evidence corpus by theme, method, chronology, mechanism, or another declared schema.

使用方法

复制安装命令，在自己的智能体环境安装前先检查源码包。
从原始文档核对所需工具、凭据和支持的宿主。
说明输入材料与期望交付物，并对照来源检查输出。

npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill categorize-evidence

开始前需了解

安装不包含模型订阅、API 额度或访问文件的权限。
仓库星数和安装量反映活跃情况，不等于独立质量或安全测试。

仓库原始内容

按源仓库内容呈现，保留标题、案例、代码、表格、链接以及原文引用的演示图片。

categorize-evidence

Purpose

Cluster an evidence corpus by a declared thematic, methodological, chronological, mechanistic, or other schema.

Input contract

yaml

required: [evidence_records, category_schema]
optional: [coding_rules, multi_label_policy, seed_categories]
constraints: [category assignments require record evidence and allow explicit multi-label or unknown states]

Procedure

Define category semantics and assignment rules.
Code each record using the declared evidence fields.
Review boundary cases and preserve multi-label or unresolved assignments.
Summarize category coverage and representative records.

If categorized sources now need claim-level structured records, consider extract-evidence-record as the next tactic.

Output contract

yaml

produces: [categorized_corpus, category_definitions, boundary_cases, coverage_summary]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]