Agent skill · research science · affaan-m
scholar-evaluation
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback. Use when evaluating academic or scientific work — papers, proposals, methods sections, or evidence quality — against a repeatable rubric.
Why this skill is useful
Provides a structured rubric for evaluating scholarly work that the AI wouldn't reliably generate on its own.
What it needs
About 3k tokens when loaded. Last updated 2026-08-06. 238,342 stars on the source repository.
What this skill does
Scholar Evaluation Use this skill to evaluate academic or scientific work with a repeatable rubric. When to Use Reviewing a research paper, proposal, thesis chapter, or literature review. Checking whether claims are supported by cited evidence. Evaluating methodology, study design, analysis, or limitations. Comparing two or more papers for quality or relevance. Producing structured feedback for revision. Evaluation Scope Start by identifying the artifact: empirical research paper theoretical paper technical report systematic or narrative literature review research proposal thesis or dissertation chapter conference abstract or short paper Then choose scope: comprehensive: all rubric dimensions targeted: one or two dimensions, such as method or citations comparative: rank multiple works against the same rubric Rubric Score each applicable dimension from 1 to 5: 5: excellent; clear, rigorous, and publication-ready 4: good; minor improvements needed 3: adequate; meaningful gaps but usable 2: weak; substantial revision needed 1: poor; major validity or clarity problems Use N/A for dimensions that do not apply. 1. Problem and Research Question Is the problem clear and specific? Is the contribution meaningful? Are scope and assumptions explicit? Does the question match the claimed contribution? 2. Literature and Context Is relevant prior work covered? Does the work synthesize rather than merely list sources? Are gaps accurately identified? Are recent and foundational sources balanced? 3. Methodology Does the method answer the research question? Are design choices justified? Are variables, datasets, participants, or materials described clearly? Could another researcher reproduce the work? Are ethical and practical constraints acknowledged? 4. Data and Evidence Are data sources credible and appropriate? Is sample size or corpus coverage adequate? Are inclusion, exclusion, and preprocessing decisions documented? Are missing data and bias risks discussed? 5. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills affaan-m/scientific-thinking-scholar-evaluation--c2c997