Borrowing it
Nothing to install: this file belongs to u9401066/med-paper-assistant. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/u9401066/med-paper-assistant/master/.claude/skills/academic-debate/SKILL.mdgit clone --depth 1 https://github.com/u9401066/med-paper-assistantWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/u9401066/med-paper-assistant/academic-debate)<a href="https://agentmods.dev/skills/u9401066/med-paper-assistant/academic-debate"><img src="https://agentmods.dev/badge/skills/u9401066/med-paper-assistant/academic-debate/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/u9401066/med-paper-assistant/academic-debate"><img src="https://agentmods.dev/badge/skills/u9401066/med-paper-assistant/academic-debate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00107 | $0.00734 |
| Opus 5 | $0.00053 | $0.00367 |
| Sonnet 5 | $0.00021 | $0.00147 |
| Haiku 4.5 | $0.00011 | $0.00073 |
Grade A, and why
academic-debate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
學術辯論與觀點比較技能
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
Framework 1: Academic Debate（雙方辯論）
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)
Framework 2: Devil's Advocate（魔鬼代言人）
系統性挑戰一個研究主張。5 面向：
- Methodological — 研究類型對應偏誤（見下方）
- Statistical — multiple comparisons, effect size, CI width, missing data, power
- Generalizability — population, setting, timeframe, intervention fidelity
- Alternative Explanations — confounding, reverse causation, temporal trends, Hawthorne
- Likely Reviewer Questions — 基於 study type
產出：Strengthening Recommendations（address counter-arguments, add sensitivity analysis, cite SR, frame conservatively）
Framework 3: Viewpoint Comparison（觀點比較）
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
Study-Type-Specific Biases
| 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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 67 lines · 107 tokens per session scan A c7dfdb46e83a
academic-debate is a skill published in the GitHub repository u9401066/med-paper-assistant (12 stars, last pushed 10d ago), licensed Apache-2.0. It adds 107 tokens to every session and 734 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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book-to-skill
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proposal-review
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