critique-manuscript
Skill39 starsChanged 8 months agoMITView on GitHub
Critique an academic manuscript for novelty, methodological rigor, causal claims, data quality, generalizability, mechanism, and presentation. Use for pre-submission review or anticipating reviewer concerns.
In this repository12 other files it gives its agents.
- accessible-pdfSkill
- anonymize-repoSkill
- arxiv-metadataSkill
- arxiv-prepSkill
- bib-doi-toggleSkill
- check-refsSkill
- critique-figuresSkill
- doi-bibtexSkill
- latex-cleanupSkill
- openalexSkill
- presubmit-checksSkill
- verify-mathSkill
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 7 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
Use a user-provided manuscript path when available.
- Distinctive: line 15
Before evaluating, establish the research question, approach, key findings, and claimed contribution.
- Distinctive: line 21
Check whether the paper engages the relevant prior work, distinguishes its contribution, and supports claims of novelty.
- Distinctive: line 27
Check whether measurements and proxies capture their stated constructs.
- Distinctive: line 35
Check representativeness, selection bias, measurement error, systematic data or method biases, temporal artifacts, reproducibility, and …
- Distinctive: line 43
Ask whether the paper explains how and why the result arises, not only what happened.
- Distinctive: line 53
Keep the critique proportional to the manuscript and venue.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Critique an academic manuscript
Review only manuscripts the user is authorized to share. If authorization is unclear, ask before reading. Do not run an external literature search unless the user requests it.
Scope
Use a user-provided manuscript path when available. Otherwise, identify the entrypoint from the project configuration and document structure, then follow included files. Read the complete argument, including figures and tables needed to evaluate its claims.
Before evaluating, establish the research question, approach, key findings, and claimed contribution. Use that understanding to test whether the manuscript's framing and evidence agree.
Review criteria
Literature and novelty
Check whether the paper engages the relevant prior work, distinguishes its contribution, and supports claims of novelty. Ask whether a reviewer could consider the result incremental or already known and whether recent or foundational references are missing.
Do not infer a confirmed literature gap from the manuscript alone. Without a search, describe the suspected gap and give concrete topics, authors, or query terms that could test it. If the user requests a search, use targeted OpenAlex queries based on the title, key claims, suspected gaps, and relevant authors or groups. Present results as papers to review, not proof that a citation is missing.
Methodological rigor
Check whether measurements and proxies capture their stated constructs; methods fit the question; baselines and null models are appropriate and up-to-date; robustness and sensitivity checks cover consequential assumptions; uncertainty is quantified; and sample size supports the analysis.
Causal claims and confounders
Identify causal language that outruns correlational evidence. Check plausible confounders, selection effects, alternative explanations, and whether hedging accurately distinguishes association from causation.
Data quality and limitations
Check representativeness, selection bias, measurement error, systematic data or method biases, temporal artifacts, reproducibility, and availability. Assess whether the limitations are discussed honestly and prominently and whether any limitation could explain the reported result.
Generalizability
Identify the populations, datasets, periods, and contexts to which the evidence applies. Check boundary conditions and whether a narrow result should be framed as a case study rather than a general claim.
Mechanism
Ask whether the paper explains how and why the result arises, not only what happened. Check whether theory or additional analysis supports the proposed mechanism and whether a simpler mechanism fits the evidence.
Clarity and presentation
Check whether the paper is clear and self-contained, the title and abstract match the actual contribution, notation is consistent, and figures and tables are informative, well-labeled, and referenced in the text. Check that the narrative has a clear question. Compare introduction claims with the results, assess whether the discussion adds interpretation rather than repetition, and judge whether length matches content.
Evidence and calibration
Anchor every finding to a section, paragraph, figure, table, or short quoted claim. Distinguish demonstrated problems from plausible alternative explanations and questions a reviewer may raise. Do not fabricate references or present suspected literature gaps as established facts.
Keep the critique proportional to the manuscript and venue. Be candid about weaknesses, preserve strengths that should survive revision, and give a concrete next step for each material issue.
Report
Return the critique in the conversation unless the user asks for a file. Organize it around:
- A neutral 1–3 sentence summary.
- The three most important risks.
- Strengths to preserve.
- Anticipated reviewer questions.
- Detailed findings under only the criteria that produced useful observations.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

