Gemini Literature Search
Search query: $ARGUMENTS
Role & Positioning
This skill uses Gemini as a broad literature discovery source:
| Skill | Source | Best for |
|---|
/arxiv | arXiv API | Latest preprints, cutting-edge unrefereed work |
/semantic-scholar | Semantic Scholar API | Published venue papers (IEEE, ACM, Springer) with citation counts |
/deepxiv | DeepXiv CLI | Layered reading: search, brief, section map, section reads |
/exa-search | Exa API | Broad web search: blogs, docs, news, companies, research papers |
/gemini-search | Gemini MCP / CLI | AI-powered broad literature discovery — searches across multiple angles, aliases, and sub-problems |
Use Gemini when you want AI-driven discovery that goes beyond keyword matching — Gemini decomposes topics into sub-problems, explores naming variants, and surfaces papers that traditional API searches may miss.
Constants
- MAX_RESULTS = 15 — Target number of papers Gemini should find.
- MIN_YEAR = 2022 — Default minimum publication year. Override with
— year: 2020-.
- DEFAULT_MODEL = auto-gemini-3 — Auto-routes within the Gemini 3 family (Pro / Flash) by server-side capacity. Required by
mcp__gemini-cli__ask-gemini and gemini-cli v0.40+; explicit gemini-3-pro-preview is silently downgraded to gemini-2.5-pro on OAuth-personal / Google One AI Pro accounts when capacity is exhausted. Override with — model: gemini-3-flash-preview (Gemini 3 Flash explicit, faster, higher quota), or — model: gemini-2.5-pro / gemini-2.5-flash (legacy, only for users on older gemini-cli < v0.40). The MCP tool accepts all of these verbatim.
Overrides (append to arguments):
/gemini-search "topic" — max: 20 — request up to 20 papers/gemini-search "topic" — year: 2020- — papers from 2020 onward/gemini-search "topic" — code-only — only papers with open-source code/gemini-search "topic" — venues: NeurIPS,ICML,ICLR — focus on specific venues/gemini-search "topic" — model: gemini-3-flash-preview — Gemini 3 Flash (faster, higher quota, less capable than Pro)/gemini-search "topic" — model: auto-gemini-3 — auto-routes within the Gemini 3 family by load/gemini-search "topic" — model: gemini-2.5-pro — legacy (only if your gemini-cli < v0.40)
Environment & Setup
Prerequisites
- Node.js v16.0.0+
- Google Gemini CLI — installed and authenticated
npm install -g @google/gemini-cli
gemini auth
- gemini-mcp-tool — MCP bridge for Claude Code (jamubc/gemini-mcp-tool)
npm install -g gemini-mcp-tool
MCP Configuration
In ~/.claude.json (or %APPDATA%\Claude\claude_desktop_config.json for Claude Desktop), add:
{
"mcpServers": {
"gemini-cli": {
"command": "gemini-mcp"
}
}
}
Alternative via npx (auto-install):
{
"mcpServers": {
"gemini-cli": {
"command": "npx",
"args": ["-y", "gemini-mcp-tool"]
}
}
}
Or one-line setup:
claude mcp add gemini-cli -- npx -y gemini-mcp-tool
Authentication
Gemini CLI uses your Google account or an API key. Add to .claude/.env:
# .claude/.env
GEMINI_API_KEY=your-key-here
Claude Code automatically loads .claude/.env as environment variables.
- Free key from Google AI Studio
- Flash model (
gemini-2.5-flash) has a generous free tier (500 req/min)
Available MCP Tools
| Tool | Parameters | Description |
|---|
mcp__gemini-cli__ask-gemini | prompt (required), model (optional), sandbox (optional) | Ask Gemini for analysis or research; supports @file syntax |
mcp__gemini-cli__sandbox-test | prompt (required), model (optional) | Safe code execution in sandbox |
mcp__gemini-cli__ping | — | Connection test |
mcp__gemini-cli__help | — | Show Gemini CLI help |
Verify Setup
gemini --version
Workflow
Step 1: Parse Arguments
Parse $ARGUMENTS for:
- query: The research topic (required)
- max: Override MAX_RESULTS
- year: Minimum publication year (e.g.,
2020-)
- code-only: Only include papers with open-source code
- venues: Comma-separated venue filter
- model: Override DEFAULT_MODEL
Step 2: Execute Search (MCP Priority)
Priority 1 — Gemini MCP (preferred):
Try calling mcp__gemini-cli__ask-gemini with the search prompt:
mcp__gemini-cli__ask-gemini({
prompt: 'You are a research literature scout. Search comprehensively for papers on: "QUERY"
IMPORTANT CONSTRAINTS:
1. Search from MULTIPLE angles — do not just use the exact query. Decompose the topic into sub-problems, aliases, neighboring tasks, and common benchmark/settings variants.
2. Prefer papers that are genuinely relevant, not merely keyword-adjacent.
3. Include top venues, journals, surveys, recent preprints, and papers with code when available.
4. Focus on papers from MIN_YEAR onward unless older foundational work is necessary.
For EACH paper found, provide ALL of the following in this exact format:
- Title: [exact title]
- Authors: [full author list]
- Year: [publication year]
- Venue: [exact conference/journal name + year, or "arXiv preprint" if not published]
- arXiv ID: [format 2401.12345, or "N/A"]
- DOI: [if available, or "N/A"]
- Code URL: [GitHub/GitLab link if available, or "No code"]
- Summary: [one-sentence core contribution]
Find at least MAX_RESULTS papers with good coverage across:
- strong recent papers from top venues
- surveys/reviews if they exist
- papers with open-source code
- closely related variants of the topic
Format as a numbered list with all fields for each paper.',
model: 'auto-gemini-3'
})
Priority 2 — Gemini CLI fallback (if MCP unavailable):
If mcp__gemini-cli__ask-gemini fails or is not configured, fall back to CLI:
gemini -p 'You are a research literature scout. Search comprehensively for papers on: "QUERY"
...same prompt as above...' 2>/dev/null
- Timeout: 120 seconds
- Stderr: Pipe to
/dev/null — contains hook warnings, not part of the response
When to use which:
- MCP is preferred because it integrates natively with Claude Code's tool system, handles model selection, and avoids shell escaping issues.
- CLI fallback ensures the skill works even when MCP is not configured or the MCP server process has crashed.
Step 3: Parse Results
Extract structured paper information from Gemini's response. For each paper, normalize to:
{
title, authors, year, venue,
arxiv_id, // "N/A" if not available
doi, // "N/A" if not available
code_url, // "No code" if not available
summary // one-sentence contribution
}
If Gemini returns fewer papers than requested, note this but do not re-query.
Step 4: Present Results
Format results as a structured table:
| # | Title | Venue | Year | Code | Summary |
|---|-------|-------|------|------|---------|
| 1 | ... | NeurIPS 2024 | 2024 | [GitHub](url) | ... |
| 2 | ... | IEEE TWC | 2023 | No | ... |
For each paper, also show:
- arXiv ID: if available (for cross-reference with
/arxiv)
- DOI: if available (canonical link for published papers)
- Code: GitHub/GitLab link or "No"
Step 5: Offer Follow-up
After presenting results, suggest:
/semantic-scholar "topic" — search published venue papers with citation counts
/arxiv "arXiv:XXXX.XXXXX" — fetch specific preprint details
/research-lit "topic" — sources: gemini, semantic-scholar — combined multi-source review
/novelty-check "idea" — verify novelty against literature
Key Rules
- MCP first, CLI second. Always try
mcp__gemini-cli__ask-gemini before falling back to gemini -p.
- Gemini is a discovery source, not a database. Its results may include papers it "knows about" from training data. Always cross-verify critical details (exact titles, venues, years) via
/semantic-scholar or /arxiv when precision matters.
- Do not use Gemini for citation counts. It may hallucinate citation numbers. Use Semantic Scholar for authoritative citation data.
- Pipe stderr to
/dev/null in CLI mode — Gemini CLI emits hook warnings on stderr.
- Timeout generously in CLI mode — Gemini's thorough search can take 30-60 seconds. Set timeout to 120s.
- If both MCP and CLI are unreachable, suggest using
/semantic-scholar, /arxiv, or /research-lit "topic" — sources: web as alternatives.