菜单
學術辯論與觀點比較框架。 LOAD THIS SKILL WHEN: debate、辯論、pro/con、正反方、devil's advocate、挑戰假設、counter-argument、反駁、compare viewpoints、比較觀點、challenge、質疑 CAPABILITIES: 純指令技能，不需要專屬 MCP tool。利用 LLM 推理能力 + 現有 tools (read_draft, search_local_references) 完成分析。
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
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用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
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npx skills add https://github.com/u9401066/med-paper-assistant --skill academic-debate命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Run multiple complementary literature searches and merge results for broad coverage. Triggers include parallel search, 並行搜尋, 廣泛搜尋.
Cross-agent workflow for evidence-grounded manuscripts, proposals, reports, student papers, and preprints with auditable gates.
Cross-agent workflow for evidence-grounded manuscripts, proposals, reports, student papers, and preprints with auditable gates.
基于 SOC 职业分类
正在显示 SKILL.md
| name | academic-debate |
| description | 學術辯論與觀點比較框架。 LOAD THIS SKILL WHEN: debate、辯論、pro/con、正反方、devil's advocate、挑戰假設、counter-argument、反駁、compare viewpoints、比較觀點、challenge、質疑 CAPABILITIES: 純指令技能，不需要專屬 MCP tool。利用 LLM 推理能力 + 現有 tools (read_draft, search_local_references) 完成分析。 |
純指令技能。LLM 結構化思考 + read_draft, search_local_references, mcp_cgu_deep_think, mcp_cgu_spark_collision。
觸發：辯論、pro/con、devil's advocate、挑戰假設、compare viewpoints
針對研究議題結構化正反方論點。按證據等級排列： SR/Meta > RCT > Cohort > Case-Control > Cross-Sectional > Case Series > Expert Opinion
輸出：Position A (supporting) → Position B (opposing) → Methodological Considerations (偏誤) → Synthesis (agreement / disagreement / clinical bottom line)
系統性挑戰一個研究主張。5 面向：
產出：Strengthening Recommendations（address counter-arguments, add sensitivity analysis, cite SR, frame conservatively）
多個理論/方法系統性比較。預設比較維度： Evidence Base, Theoretical Foundation, Clinical Applicability, Patient Safety, Cost-Effectiveness, Current Guidelines, Limitations
| Type | Key Biases |
|---|---|
| RCT | Selection, performance, detection, attrition, reporting |
| Cohort | Selection, confounding, information, loss to follow-up, healthy worker |
| Case-Control | Recall, selection (controls), confounding, misclassification, temporal ambiguity |
| Cross-Sectional | No temporality, prevalence-incidence, non-response, information |
| Retrospective | Information (records), survivorship, confounding, missing data |
Auto-detect：randomized/RCT=RCT, cohort/prospective=Cohort, case-control/odds=Case-Control, cross-sectional/prevalence=Cross-Sectional, retrospective/chart=Retrospective