Academic Paper Review
Structured critical review of a paper (method, claims, threats to validity) in the voice of a third reviewer.
🧠 Why it works
Paper review failure modes are well-studied: vague praise, missing the actual contribution, or surfacing nits while ignoring a broken methodology. Constraining the LLM to a taxonomy that requires a claim-evidence mapping forces it to either cite a line number or stay silent — which matches what a competent reviewer does. The 'Reviewer 3' voice also counterbalances the model's default sycophancy bias.
⚙️ How it works
1) Extract abstract + method + results via the PDF Structure Extraction skill. 2) For each of the 6 review categories, ask Claude to produce claim-evidence pairs quoting line numbers from the extracted text. 3) Empty categories become 'No concerns' rather than filler. 4) Generate an aggregate score (Weak Accept / Weak Reject / Borderline) justified by the count and severity of concerns. 5) Output is reviewer-form-ready markdown plus a side-by-side change-request table.
Description
A review skill that produces a Reviewer 3-style critique: summary, strengths, concerns bucketed by category (method / stats / novelty / reproducibility), and concrete revision asks. Calibrated against NeurIPS / ICLR reviewer guidelines.
Install this skill
A Claude skill is a skill.md file with YAML frontmatter and a markdown body.
Drop the file into your tool of choice — or pick a different format if you use Cursor, Windsurf, Copilot, or something else.
mkdir -p ~/.claude/skills/academic-paper-review \
&& curl -L https://aidiveforge.com/skill/academic-paper-review.skill-md \
-o ~/.claude/skills/academic-paper-review/skill.mdSave to ~/.claude/skills/academic-paper-review/skill.md
Recommended Use
Sign in to suggestTools and workflow packs this skill pairs well with. Forge picks are auto-generated from category + capability signals; Community picks are added by people who've used the pairing.
Forge Auto-recommended matches
Workflow packs
-
Product Documentation & Knowledge Base post 31%
Auto-generate comprehensive product documentation, API guides, and internal wikis from code and specs—reducing documentation debt and keeping content in sync with product changes.
Why: caps 0/0 · io-match · name-mention
-
Multilingual Content Localization post 31%
Convert English content into multiple languages with culturally adapted audio and subtitled videos. Reach global audiences in 2-3 hours instead of weeks of manual translation.
Why: caps 0/0 · io-match · name-mention
Report compatibility
Tell the community which tool you used this skill with, and whether it worked.
Suggest a pairing
Recommend a tool or workflow pack that this skill works well with. Up to 5 recommendations per day.