Lit Screen

lit-screen (Stage 6 -- Abstract Screening)

Screen every paper's abstract against the original research prompt. In the orchestrator's agent-driven flow the relevance judgment is produced by Opus subagents through the --emit-tasks / --ingest-results seam (no API key); a standalone run uses the in-script Claude Sonnet API path instead. Produces a relevance score (1-10), rationale, and structured tags for each paper.

Usage

python ~/.claude/skills/lit-screen/scripts/lit_screen.py \
  --input stage5_merged.json \
  --query "your research prompt here" \
  -o stage6_screened.json

CLI Flags

| Flag | Default | Description | |------|---------|-------------| | --input | (required) | Input JSON from Stage 5 (dedup output) | | --query | (required) | Research query/prompt to screen against | | -o, --output | stage6_screened.json | Output JSON path | | --model | claude-sonnet-4-6 | Anthropic model ID (autonomous fallback) | | --concurrency | 5 | Max simultaneous API requests (autonomous fallback) | | --emit-tasks PATH | — | Agent-driven: write per-paper screening tasks and stop (no API) | | --ingest-results PATH | — | Agent-driven: merge Opus screening results and write all outputs (no API) |

Output Schema

Each paper gets these fields added:

{
  "screening_score": 8,
  "screening_rationale": "Directly examines board composition changes...",
  "paper_type": "empirical",
  "identification_strategy": "DiD",
  "relationship": "direct competitor"
}

Output Files

1. JSON: stage6_screened.json -- full paper list with screening fields
2. JSON: stage6_filtered.json -- papers with score >= 4 only
3. XLSX: stage6_screened.xlsx -- all papers, sorted by screening_score descending
4. XLSX: stage6_filtered.xlsx -- filtered papers (score >= 4), sorted by score descending
5. RIS: stage6_screened.ris -- for import into reference managers
6. BIB: stage6_screened.bib -- BibTeX entries for papers with score >= 5

Environment Variables

| Var | Required | Description | |-----|----------|-------------| | ANTHROPIC_API_KEY | Fallback | Standalone-run screening (Sonnet API). The agent-driven flow screens with Opus subagents and needs no key. |

Field Values

• screening_score: 1 (irrelevant) to 10 (highly relevant); 0 = no abstract
• paper_type: theoretical or empirical
• identification_strategy: natural experiment, IV, DiD, RDD, structural, descriptive, N/A
• relationship: foundational/must-cite, same method different context, same context different method, direct competitor, methodological reference, tangential

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: kennethkhoocy
• Source: kennethkhoocy/legal-scholarship-skills
• License: MIT

Install and usage instructions live in the source repository linked above.