Deep Research Skill

Perform deep research powered by Google Gemini's deep research agent. Upload documents to file search stores for RAG-grounded answers. Manage research sessions with persistent workspace state.

For AI Agents

Get a full capabilities manifest, decision trees, and output contracts:

uv run {baseDir}/scripts/onboard.py --agent

See AGENTS.md for the complete structured briefing.

Security & Transparency

Credentials: This skill requires a Google/Gemini API key (one of GOOGLE_API_KEY, GEMINI_API_KEY, or GEMINI_DEEP_RESEARCH_API_KEY). The key is read from environment variables and passed to the google-genai SDK. It is never logged, written to files, or transmitted anywhere other than the Google Gemini API.

File uploads: The --context flag uploads local files to Google's ephemeral file search stores for RAG grounding. Sensitive files are automatically excluded: .env*, credentials.json, secrets.*, private keys (.pem, .key), and auth tokens (.npmrc, .pypirc, .netrc). Binary files are rejected by MIME type filtering. Build directories (node_modules, __pycache__, .git, dist, build) are skipped. The ephemeral store is auto-deleted after research completes unless --keep-context is specified. Use --dry-run to preview what would be uploaded without sending anything. Only files you explicitly point --context at are uploaded -- no automatic scanning of parent directories or home folders.

Non-interactive mode: When stdin is not a TTY (agent/CI use), confirmation prompts are automatically skipped. This is by design for agent integration but means an autonomous agent with file system access could trigger uploads. Restrict the paths agents can access, or use --dry-run and --max-cost guards.

No obfuscation: All code is readable Python with PEP 723 inline metadata. No binary blobs, no minified scripts, no telemetry, no analytics. The full source is auditable at github.com/24601/agent-deep-research.

Local state: Research session state is written to .gemini-research.json in the working directory. This file contains interaction IDs, store mappings, and upload hashes -- no credentials or research content. Use state.py gc to clean up orphaned stores from crashed runs.

Prerequisites

• A Google API key (GOOGLE_API_KEY or GEMINI_API_KEY environment variable)
• uv installed (see uv install docs)

Quick Start

# Run a deep research query
uv run {baseDir}/scripts/research.py "What are the latest advances in quantum computing?"

# Check research status
uv run {baseDir}/scripts/research.py status <interaction-id>

# Save a completed report
uv run {baseDir}/scripts/research.py report <interaction-id> --output report.md

# Research grounded in local files (auto-creates store, uploads, cleans up)
uv run {baseDir}/scripts/research.py start "How does auth work?" --context ./src --output report.md

# Export as HTML or PDF
uv run {baseDir}/scripts/research.py start "Analyze the API" --context ./src --format html --output report.html

# Auto-detect prompt template based on context files
uv run {baseDir}/scripts/research.py start "How does auth work?" --context ./src --prompt-template auto --output report.md

Environment Variables

Set one of the following (checked in order of priority):

Optional model configuration:

Research Commands

Start Research

uv run {baseDir}/scripts/research.py start "your research question"

The start subcommand is the default, so research.py "question" and research.py start "question" are equivalent.

Important: When --output or --output-dir is used, the command blocks until research completes (2-10+ minutes). Do not background it with &. Use non-blocking mode (omit --output) to get an ID immediately, then poll with status and save with report.

Check Status

uv run {baseDir}/scripts/research.py status <interaction-id>

Returns the current status (in_progress, completed, failed) and outputs if available.

Save Report

uv run {baseDir}/scripts/research.py report <interaction-id>

Structured Output (--output-dir)

When --output-dir is used, results are saved to a structured directory:

<output-dir>/
  research-<id>/
    report.md          # Full final report
    metadata.json      # Timing, status, output count, sizes
    interaction.json   # Full interaction data (all outputs, thinking steps)
    sources.json       # Extracted source URLs/citations

A compact JSON summary (under 500 chars) is printed to stdout:

{
  "id": "interaction-123",
  "status": "completed",
  "output_dir": "research-output/research-interaction-1/",
  "report_file": "research-output/research-interaction-1/report.md",
  "report_size_bytes": 45000,
  "duration_seconds": 154,
  "summary": "First 200 chars of the report..."
}

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