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sr-screener

An AI agent skill from Imbad0202/academic-research-skills, scored 70 out of 100 by code.

70/ 100B

Code score by group

  • Spec18/20
  • Description14/20
  • Procedure10/15
  • Done criteria4/15
  • Resources7/10
  • Scripts6/8
  • Safety7/7
  • Upkeep4/5

It loses the most points in Done criteria (11), the group that checks whether there is a checklist and a step that verifies the work.

What the author says it does

Protocol-driven study screening for systematic, scoping and rapid reviews. Turns a proposal or PROSPERO protocol into confirmed eligibility rules, then screens titles/abstracts and full texts with two blinded AI reviewers and a third-reviewer adjudicator: ordered exclusion codes, no silent defaults, resumable batch runs, QC (seed studies, near-miss rechecks, kappa and PABAK), PRISMA 2020 counts, EndNote/Zotero RIS groups, an Excel log, a methods draft and a literature_corpus handoff to academic-paper. Reads RIS, PubMed .nbib, Web of Science and CSV exports; removes duplicates. 8 modes: protoc…

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

Repository
Imbad0202/academic-research-skills
Folder
sr-screener
License
Not identified by GitHub
GitHub stars
56,600
SKILL.md lines
517
Other files
24

Add sr-screener to your agent

npx skills add Imbad0202/academic-research-skills --skill sr-screener

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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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.