Individual skill
scholar-evaluation
Implements the ScholarEval framework to evaluate scholarly documents; trigger when the user provides a PDF/DOCX/TXT file or pasted text and requests critique, scoring, or quality assessment.
scientific-skills/Evidence Insight/scholar-evaluation/SKILL.md
Source commit 686e09dfdb45d9fa1a08664f06bb93769b3c9d91
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- bioinformatics Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- ai Repository topic
- biology Repository topic
- cancer-genomics Repository topic
- data-visualization Repository topic
- differential-expression Repository topic
- genomics Repository topic
- medical Repository topic
- engineering Derived category
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SKILL.mdcore · 3,743 bytesSKILL.mdcore · 3,743 bytesSKILL.mdcore · 3,743 bytesSKILL.mdcore · 3,743 bytesSKILL.mdcore · 3,743 bytesreferences/evaluation_framework.mddoc · 2,133 bytesrequirements.txtdoc · 25 bytesscholar-evaluation_audit_result_v1.jsonasset · 13,084 bytesscores.jsonasset · 188 bytesscripts/calculate_scores.pyruns · 2,248 bytesscripts/extract_text.pyruns · 3,384 bytes
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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
## When to Use
- Evaluate a research paper, thesis, or proposal and produce a structured critique with scores.
- Generate actionable revision recommendations across core academic writing dimensions.
- Compare multiple drafts/versions of a manuscript using consistent rubric-based scoring.
- Assess submission readiness (e.g., for a conference/journal) and identify major weaknesses.
- Review a document provided as a PDF/DOCX/TXT file when the user expects automatic text extraction.
## Key Features
- **Automatic text extraction** from **PDF/DOCX/TXT** via `scripts/extract_text.py` (intended as the first step for file inputs).
- **ScholarEval rubric** with **8 evaluation dimensions** (see `references/evaluation_framework.md`).
- **Per-dimension scoring (1–5)** with qualitative feedback and concrete recommendations.