yogsoth-ai
yogsoth-ai/de-anthropocentric-research-engine
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。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill reproducibility-checklist-audit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。
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Strategy: Dialectic engine retuned for truth-seeking, not survival. A defender steelmans a claim into its MOST falsifiable form, a critic attacks to refute it, a judge classifies the exchange into BROKEN/CORROBORATED/UNFALSIFIABLE — the judge does NOT pick a winner or score persuasiveness. Methods: Irving debate (repurposed), Toulmin argumentation, Mayo severe testing.
Campaign: Logical extreme and boundary testing via reductio ad absurdum and edge-case analysis. Core question: Does this artifact collapse under logical limits and boundary conditions? Methods: Lakatos 1976, Dutilh Novaes 2016, BVA, Flyvbjerg Critical Case, Popper.
Campaign for mapping argument structures — extract claims, link evidence, assess strength, synthesize positions. Produces argument graphs in the wiki vault.
基于 SOC 职业分类
| name | reproducibility-checklist-audit |
| description | Assess paper completeness against ML Reproducibility Checklist |
| execution | subagent |
| prompt | ./prompt.md |
| input | paper_content |
Evaluate a paper against the standard ML Reproducibility Checklist (as used by NeurIPS, ICML, ICLR). Produces a structured assessment of what information is present, what is missing, and an overall reproducibility score.
| Field | Type | Description |
|---|---|---|
| paper_content | string | Full paper text (markdown format) |
{
"paper_title": "string",
"checklist": {
"model_architecture": {"present": true, "details": "string"},
"training_procedure": {"present": true, "details": "string"},
"hyperparameters": {"present": true, "details": "string"},
"hyperparameter_search": {"present": false, "details": "string"},
"datasets": {"present": true, "details": "string"},
"data_preprocessing": {"present": true, "details": "string"},
"evaluation_metrics": {"present": true, "details": "string"},
"error_bars_or_confidence": {"present": false, "details": "string"},
"number_of_runs": {"present": false, "details": "string"},
"compute_resources": {"present": false, "details": "string"},
"code_availability": {"present": true, "details": "string"},
"random_seeds": {"present": false, "details": "string"}
},
"overall_score": 0.0,
"critical_gaps": ["string"],
"reproducibility_risk": "low|medium|high|critical"
}