research-lit

name	research-lit
description	Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.

Research Literature Review

Research topic: $ARGUMENTS

Constants

• GEMINI_SCOUT_PRIMARY = true — Use Gemini via the local gemini-research MCP bridge as the primary literature scout and triage engine.
• PAPER_LIBRARY — Local directory containing user's paper collection (PDFs). Check these paths in order:
  1. papers/ in the current project directory
  2. literature/ in the current project directory
  3. Custom path specified by user in AGENTS.md under ## Paper Library
• MAX_LOCAL_PAPERS = 20 — Maximum number of local PDFs to scan (read first 3 pages each). If more are found, prioritize by filename relevance to the topic.
• ARXIV_DOWNLOAD = false — When true, download top 3-5 most relevant arXiv PDFs to PAPER_LIBRARY after search. When false (default), only fetch metadata (title, abstract, authors) via arXiv API — no files are downloaded.
• ARXIV_MAX_DOWNLOAD = 5 — Maximum number of PDFs to download when ARXIV_DOWNLOAD = true.

💡 Overrides:

• /research-lit "topic" — paper library: ~/my_papers/ — custom local PDF path
• /research-lit "topic" — sources: zotero, local — only search Zotero + local PDFs
• /research-lit "topic" — sources: zotero — only search Zotero
• /research-lit "topic" — sources: web — only search the web (skip all local)
• /research-lit "topic" — sources: deepxiv — only search via DeepXiv progressive retrieval
• /research-lit "topic" — sources: all, deepxiv — use default sources plus DeepXiv
• /research-lit "topic" — arxiv download: true — download top relevant arXiv PDFs
• /research-lit "topic" — arxiv download: true, max download: 10 — download up to 10 PDFs

Gemini-First Policy

For literature search and literature review tasks, Gemini is the default search/review engine.

Use Gemini first to:

• search Zotero-backed literature when available
• build a compact core paper set
• add a small recent-paper correction set
• explain why each paper matters before any broad local/tool sweep

Use local PDFs, arXiv scripts, DeepXiv, and web search as:

• targeted fetch/retrieval tools
• verification tools
• fallback paths if Gemini is unavailable or incomplete

Data Sources

This skill checks multiple sources in priority order. All are optional — if a source is not configured or not requested, skip it silently.

Source Selection

Parse $ARGUMENTS for a — sources: directive:

• If — sources: is specified: Only search the listed sources (comma-separated). Valid values: zotero, obsidian, local, web, deepxiv, exa, all.
• If not specified: Default to all — search every available source in priority order (deepxiv and exa are excluded from all; they must be explicitly listed).

Examples:

/research-lit "diffusion models"                        → all (default)
/research-lit "diffusion models" — sources: all         → all
/research-lit "diffusion models" — sources: zotero      → Zotero only
/research-lit "diffusion models" — sources: zotero, web → Zotero + web
/research-lit "diffusion models" — sources: local       → local PDFs only
/research-lit "topic" — sources: obsidian, local, web   → skip Zotero
/research-lit "topic" — sources: deepxiv                → DeepXiv only
/research-lit "topic" — sources: all, deepxiv           → default sources + DeepXiv
/research-lit "topic" — sources: exa                    → Exa only (broad web + content extraction)
/research-lit "topic" — sources: all, exa               → default sources + Exa web search

Source Table

Priority	Source	ID	How to detect	What it provides
1	Zotero (via MCP)	zotero	Try calling any mcp__zotero__* tool — if unavailable, skip	Collections, tags, annotations, PDF highlights, BibTeX, semantic search
2	Obsidian (via MCP)	obsidian	Try calling any mcp__obsidian-vault__* tool — if unavailable, skip	Research notes, paper summaries, tagged references, wikilinks
3	Local PDFs	local	Glob: papers/**/*.pdf, literature/**/*.pdf	Raw PDF content (first 3 pages)
4	Web search	web	Always available (WebSearch)	arXiv, Semantic Scholar, Google Scholar
5	DeepXiv CLI	deepxiv	tools/deepxiv_fetch.py and installed deepxiv CLI	Progressive paper retrieval: search, brief, head, section, trending, web search. Only runs when explicitly requested
6	Exa Search	exa	tools/exa_search.py and installed exa-py SDK	AI-powered broad web search with content extraction (highlights, text, summaries). Covers blogs, docs, news, companies, and research papers beyond arXiv/S2. Only runs when explicitly requested

Graceful degradation: If no MCP servers are configured, the skill works exactly as before (local PDFs + web search). Zotero and Obsidian are pure additions.

Workflow

Step 0: Gemini literature scout first

Before doing any broad local or web sweep, ask Gemini to produce a literature evidence packet for the topic.

Prefer this route in Codex:

• mcp__gemini-research__literature_search_start for long-running searches
• mcp__gemini-research__literature_search_status to poll until completion
• mcp__gemini-research__literature_search when you want a direct synchronous result

Default Gemini request:

• Use Zotero as the primary evidence base if available
• Curate 8-12 core papers grouped as:
  • closest prior work
  • strongest baselines
  • same-tier venue exemplars
  • key evidence/mechanism references
• Add 3-5 highly relevant recent papers not already in the Zotero core set
• Return a compact table with title, venue, year, why-relevant, and whether the paper is already in Zotero

Only after Gemini returns this packet should you scan local files or fetch specific papers.

Step 0a: Search Zotero Library (if available)

Skip this step entirely if Zotero MCP is not configured.

Try calling a Zotero MCP tool (e.g., search). If it succeeds:

1. Search by topic: Use the Zotero search tool to find papers matching the research topic
2. Read collections: Check if the user has a relevant collection/folder for this topic
3. Extract annotations: For highly relevant papers, pull PDF highlights and notes — these represent what the user found important
4. Export BibTeX: Get citation data for relevant papers (useful for /paper-write later)
5. Compile results: For each relevant Zotero entry, extract:
   • Title, authors, year, venue
   • User's annotations/highlights (if any)
   • Tags the user assigned
   • Which collection it belongs to

📚 Zotero annotations are gold — they show what the user personally highlighted as important, which is far more valuable than generic summaries.

Step 0b: Search Obsidian Vault (if available)

Skip this step entirely if Obsidian MCP is not configured.

Try calling an Obsidian MCP tool (e.g., search). If it succeeds:

1. Search vault: Search for notes related to the research topic
2. Check tags: Look for notes tagged with relevant topics (e.g., #diffusion-models, #paper-review)
3. Read research notes: For relevant notes, extract the user's own summaries and insights
4. Follow links: If notes link to other relevant notes (wikilinks), follow them for additional context
5. Compile results: For each relevant note:
   • Note title and path
   • User's summary/insights
   • Links to other notes (research graph)
   • Any frontmatter metadata (paper URL, status, rating)

📝 Obsidian notes represent the user's processed understanding — more valuable than raw paper content for understanding their perspective.

Step 0c: Scan Local Paper Library

Before searching online, check if the user already has relevant papers locally:

1. Locate library: Check PAPER_LIBRARY paths for PDF files

   Glob: papers/**/*.pdf, literature/**/*.pdf
   

2. De-duplicate against Zotero: If Step 0a found papers, skip any local PDFs already covered by Zotero results (match by filename or title).

3. Filter by relevance: Match filenames and first-page content against the research topic. Skip clearly unrelated papers.

4. Summarize relevant papers: For each relevant local PDF (up to MAX_LOCAL_PAPERS):

   • Read first 3 pages (title, abstract, intro)
   • Extract: title, authors, year, core contribution, relevance to topic
   • Flag papers that are directly related vs tangentially related

5. Build local knowledge base: Compile summaries into a "papers you already have" section. This becomes the starting point — external search fills the gaps.

📚 If no local papers are found, skip to Step 1. If the user has a comprehensive local collection, the external search can be more targeted (focus on what's missing).

Step 1: Search (external, targeted fallback/verification)

• Use WebSearch to find recent papers on the topic
• Check arXiv, Semantic Scholar, Google Scholar
• Focus on papers from last 2 years unless studying foundational work
• De-duplicate: Skip papers already found in Zotero, Obsidian, or local library
• Use this step to verify, expand, or fetch around the Gemini-generated evidence packet rather than starting from scratch

arXiv API search (always runs, no download by default):

Locate the fetch script and search arXiv directly:

# Try to find arxiv_fetch.py
SCRIPT=$(find tools/ -name "arxiv_fetch.py" 2>/dev/null | head -1)
# If not found, check the shared skill install
[ -z "$SCRIPT" ] && SCRIPT=$(find ~/.codex/skills/arxiv/ -name "arxiv_fetch.py" 2>/dev/null | head -1)

# Search arXiv API for structured results (title, abstract, authors, categories)
python3 "$SCRIPT" search "QUERY" --max 10

If arxiv_fetch.py is not found, fall back to WebSearch for arXiv (same as before).

The arXiv API returns structured metadata (title, abstract, full author list, categories, dates) — richer than WebSearch snippets. Merge these results with WebSearch findings and de-duplicate.

DeepXiv search (only when deepxiv is in sources):

When the user explicitly requests — sources: deepxiv (or includes deepxiv in a combined source list), use the DeepXiv adapter for progressive retrieval:

python3 tools/deepxiv_fetch.py search "QUERY" --max 10
python3 tools/deepxiv_fetch.py paper-brief ARXIV_ID
python3 tools/deepxiv_fetch.py paper-head ARXIV_ID
python3 tools/deepxiv_fetch.py paper-section ARXIV_ID "Experiments"

If tools/deepxiv_fetch.py or the deepxiv CLI is unavailable, skip this source gracefully and continue with the remaining requested sources.

De-duplication against other sources:

• Match by arXiv ID first
• Fall back to normalized title when needed
• Keep one canonical paper entry and record deepxiv as an additional source when it overlaps with web/arXiv findings

Exa search (only when exa is in sources):

When the user explicitly requests — sources: exa (or includes exa in a combined source list), use the Exa tool for broad AI-powered web search with content extraction:

EXA_SCRIPT=$(find tools/ -name "exa_search.py" 2>/dev/null | head -1)

# Search for research papers with highlights
python3 "$EXA_SCRIPT" search "QUERY" --max 10 --category "research paper" --content highlights

# Search for broader web content (blogs, docs, news)
python3 "$EXA_SCRIPT" search "QUERY" --max 10 --content highlights

If tools/exa_search.py or the exa-py SDK is unavailable, skip this source gracefully and continue with the remaining requested sources.

De-duplication against other sources:

• Match by URL first, then normalized title
• If Exa returns an arXiv paper already found by other sources, prefer structured metadata from arXiv/S2
• Exa results from non-academic domains (blogs, docs, news) are unique value not covered by other sources

Optional PDF download (only when ARXIV_DOWNLOAD = true):

After all sources are searched and papers are ranked by relevance:

# Download top N most relevant arXiv papers
python3 "$SCRIPT" download ARXIV_ID --dir papers/

• Only download papers ranked in the top ARXIV_MAX_DOWNLOAD by relevance
• Skip papers already in the local library
• 1-second delay between downloads (rate limiting)
• Verify each PDF > 10 KB

Step 2: Analyze Each Paper

For each relevant paper (from all sources), extract:

• Problem: What gap does it address?
• Method: Core technical contribution (1-2 sentences)
• Results: Key numbers/claims
• Relevance: How does it relate to our work?
• Source: Where we found it (Zotero/Obsidian/local/web) — helps user know what they already have vs what's new

Step 3: Synthesize

• Group papers by approach/theme
• Identify consensus vs disagreements in the field
• Find gaps that our work could fill
• If Obsidian notes exist, incorporate the user's own insights into the synthesis

Step 4: Output

Present as a structured literature table:

| Paper | Venue | Method | Key Result | Relevance to Us | Source |
|-------|-------|--------|------------|-----------------|--------|

Plus a narrative summary of the landscape (3-5 paragraphs).

If Zotero BibTeX was exported, include a references.bib snippet for direct use in paper writing.

Step 5: Save (if requested)

• Save paper PDFs to literature/ or papers/
• Update related work notes in project memory
• If Obsidian is available, optionally create a literature review note in the vault

Key Rules

• Always include paper citations (authors, year, venue)
• Distinguish between peer-reviewed and preprints
• Be honest about limitations of each paper
• Note if a paper directly competes with or supports our approach
• Never fail because a MCP server is not configured — always fall back gracefully to the next data source
• Zotero/Obsidian tools may have different names depending on how the user configured the MCP server (e.g., mcp__zotero__search or mcp__zotero-mcp__search_items). Try the most common patterns and adapt.