mcpbeat

Screening Manager

willoscar/screening-manager

| Use when an approved `evidence-review` protocol needs to be applied to a candidate pool.

1k tokens
context cost
the whole folder, loaded on every use
2
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
496
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository 
npx skills add https://github.com/WILLOSCAR/research-units-pipeline-skills --skill screening-manager

What comes with it

3 760 bytes besides the instruction
scripts/run.py

The instruction itself

7 sections, as written by the author

Screening Manager

Transforms an approved protocol plus candidate pool into an auditable screening log.

Inputs

Required:

  • output/PROTOCOL.md

Candidate pool:

  • papers/papers_raw.jsonl
  • papers/papers_dedup.jsonl
  • or papers/core_set.csv

Output

  • papers/screening_log.csv

Contract

Each row must include at least:

  • paper_id
  • title
  • year
  • url
  • decision
  • reason
  • reason_codes
  • reviewer
  • decided_at

Script boundary

scripts/run.py should:

  • parse protocol clauses
  • choose the current candidate pool
  • emit one deterministic row per candidate

It should not invent new protocol rules.

Acceptance

  • output exists
  • every candidate has one row
  • every row has decision plus protocol-grounded reason code

Non-goals

  • full-text extraction
  • synthesis writing

How to use it

Copy the folder

Take willoscar/screening-manager from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.