Claude Skill MartBrowse skillsQuick linesLearn by videoTerminal guideWhat is a Skill?
Back to list

Literature Review Agent (PaperOrchestra Step 3)

Discovers candidate papers via web search, verifies them through Semantic Scholar plus Crossref/OpenAlex cross-checks, and drafts a cited Introduction + Related Work with a matching refs.bib.

EducationAdvanced64491AI score 9/10Last updated: Aug 9, 2026

What it does

Implements Step 3 of the PaperOrchestra paper-writing pipeline.

  • Phase 1 — Discovery: runs the search directions and Related Work cluster queries from outline.json through your host's web search (WebSearch, or optional Exa / Tavily backends) to collect candidate papers.
  • Pre-dedup: pre_dedup_candidates.py removes duplicate candidates up front, saving 30–40% of the Semantic Scholar quota.
  • Phase 2 — Verification: sequential, cached, 1 QPS S2 lookups with Levenshtein title match > 70, non-empty abstract requirement, and a venue-derived temporal cutoff; then dedup by paperId.
  • Cross-index check: re-verifies every paper against Crossref and OpenAlex and grades each as high / medium / low / conflict to surface hallucinated citations (a WARN gate, not a hard block).
  • Outputs: citation_pool.json, refs.bib, and intro_relwork.tex citing ≥90% of the verified pool, enforced by a coverage gate.

Who it's for

  • Researchers and grad students writing to a conference deadline (CVPR, ICLR, NeurIPS)
  • Anyone burned by LLM-fabricated references
  • Teams automating bibliography construction and Related Work drafting
  • Users running the full PaperOrchestra pipeline

Examples

  1. "Find citations for my paper" → executes discovery queries and produces a verified pool plus refs.bib.
  2. "Draft the related work section" → writes LaTeX Introduction + Related Work citing at least 90% of the pool, with timeline and evaluation guardrails.
  3. "Check my bibliography for hallucinated citations" → runs cross_verify.py and returns a tiered corroboration report.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/Ar9av/PaperOrchestra/HEAD/skills/literature-review-agent/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/literature-review-agent folder from the GitHub repo Ar9av/PaperOrchestra into my ~/.claude/skills/literature-review-agent/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/Ar9av/PaperOrchestra.git /tmp/PaperOrchestra && mkdir -p ~/.claude/skills && cp -r /tmp/PaperOrchestra/skills/literature-review-agent ~/.claude/skills/

This is a third-party skill. Check the source repository before installing.

  1. Open a terminal.
  2. Clone the repo: git clone https://github.com/Ar9av/PaperOrchestra.git
  3. Create the skills directory: mkdir -p ~/.claude/skills
  4. Copy the skill: cp -r PaperOrchestra/skills/literature-review-agent ~/.claude/skills/
  5. Recommended — also copy the orchestrator and shared resources it references: cp -r PaperOrchestra/skills/paper-orchestra PaperOrchestra/skills/shared ~/.claude/skills/
  6. Make sure Python 3 and the script dependencies (e.g. requests) are installed.
  7. Optional API keys: export SEMANTIC_SCHOLAR_API_KEY=..., export EXA_API_KEY=... or export TAVILY_API_KEY=..., and export PAPER_ORCHESTRA_MAILTO=you@example.com
  8. Restart Claude Code and ask: "Find citations for my paper and draft the related work."
View source on GitHubLicense: NOASSERTION