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academic-paper-reviewer

An AI agent skill from Imbad0202/academic-research-skills, scored 72 out of 100 by code.

72/ 100B

Code score by group

  • Spec18/20
  • Description13/20
  • Procedure15/15
  • Done criteria8/15
  • Resources5/10
  • Scripts2/8
  • Safety7/7
  • Upkeep4/5

It loses the most points in Description (7), the group that checks whether the description says what the skill does and when to use it.

What the author says it does

Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer…

This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.

Repository
Imbad0202/academic-research-skills
Folder
academic-paper-reviewer
License
Not identified by GitHub
GitHub stars
56,600
SKILL.md lines
554
Other files
27

Add academic-paper-reviewer to your agent

npx skills add Imbad0202/academic-research-skills --skill academic-paper-reviewer

The command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored. GitHub identifies no license for this repository, so check its terms before you use it.

Labelled for

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  3. academic-paper

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  4. deep-research

    Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 8 modes: full research, quick brief, paper review, lit-review, fact-check, three…

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All skills in Imbad0202/academic-research-skills

Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.