deep-research
An AI agent skill from Imbad0202/academic-research-skills, scored 60 out of 100 by code.
Code score by group
It loses the most points in Description (12), the group that checks whether the description says what the skill does and when to use it.
What the author says it does
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-way literature scan, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature…
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- Imbad0202/academic-research-skills
- Folder
- deep-research
- License
- Not identified by GitHub
- GitHub stars
- 56,600
- SKILL.md lines
- 730
- Other files
- 52
Add deep-research to your agent
npx skills add Imbad0202/academic-research-skills --skill deep-research
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.
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sr-screener
Protocol-driven study screening for systematic, scoping and rapid reviews. Turns a proposal or PROSPERO protocol into confirmed eligibility rules, then screens titles/abstracts an…
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academic-paper
12-agent academic paper writing pipeline. 11 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure/rebuttal-audit). 6 paper…
62C
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.