Sr Screener
Protocol-driven study screening for systematic, scoping and rapid reviews.
Install
npx skills add Imbad0202/academic-research-skills --skill sr-screener -g -a claude-code -y- Repository
- Imbad0202/academic-research-skills54.9k
- Category
- Documents
- Updated
- 3d ago
- License
- See repository
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- Yes, review before use
What 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: protocol, quick, pilot, ta-screen, ft-screen, adjudicate, audit, report. Use it to screen records against eligibility criteria, pilot screening, resolve screening conflicts, audit exclusions or report the selection process. Triggers on: screen these papers, title/abstract screening, full-text screening, screening conflicts, inclusion criteria, PRISMA flow, غربالگری مقالات, اسکرینینگ عنوان و چکیده, معیارهای ورود و خروج.
SR-Screener v1.0.0, Protocol-Driven Screening Decisions
Screening is where a systematic review quietly loses studies: criteria drift, tired reviewers, records that fall between two batches. This skill makes each screening decision explicit and traceable. The criteria are fixed before any record is read, every record gets two independent decisions, disagreements go to a third reviewer, nothing is ever decided by default, and every number in the PRISMA flow can be traced to a file. The AI reviewers support the review team; people sign off on the final screening.
The skill sits between deep-research (question, protocol, search) and academic-paper
(writing the review). Dual review at scale uses the Workflow tool (or one Agent call per batch);
small sets work in a single session. The deterministic steps are Python scripts in this skill's
scripts/ folder (Python 3.9+, standard library only; openpyxl is optional and gives an Excel
log instead of CSV files).
Routing discipline (v3.9.2): plugin and skills-copy installs do not load this repository's
.claude/CLAUDE.md, so its routing core is repeated below, identical toshared/references/routing_core.md(#892). If routing has not settled when this skill loads, apply the core before dispatching any agent.
