lit-dedup
Stage 5 of the lit review pipeline: merge and deduplicate papers from all prior stages (Undermind, Scholar Labs, supplementary search) into a single master list with provenance tracking. Two-pass dedup: exact DOI match then LLM fuzzy match via DeepSeek/Claude. Only use this skill when explicitly requested — e.g., the user says "run lit-dedup", "lit-dedup", or "/lit-dedup". Do NOT auto-trigger on general literature review requests.
npx skills add kennethkhoocy/applied-micro-skills --skill lit-dedup --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Lit-Dedup (Stage 5 — Merge & Deduplicate) Merge multiple pipeline stage outputs into one deduplicated master list with provenance tracking. **Input**: one or more JSON files from Stages 1–4 **Output**: `merged_results.json` + `merged_results.ris` + `dedup_log.json` ## Quick Start ```bash # Merge all JSON files in a directory python scripts/lit_dedup.py --input-dir ./results/ -o merged_results.js
What does the lit-dedup skill do?
Stage 5 of the lit review pipeline: merge and deduplicate papers from all prior stages (Undermind, Scholar Labs, supplementary search) into a single master list with provenance tracking. Two-pass dedup: exact DOI match then LLM fuzzy match via DeepSeek/Claude. Only use this skill when explicitly requested — e.g., the user says "run lit-dedup", "lit-dedup", or "/lit-dedup". Do NOT auto-trigger on general literature review requests.
How do I install it?
Run `npx skills add kennethkhoocy/applied-micro-skills --skill lit-dedup --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From kennethkhoocy/applied-micro-skills, a repository with 54 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.