Gemini Deep Research
Use this skill for Gemini Deep Research Agent or Gemini search-grounded research flows. Gemini Deep Research is useful when research should be grounded in Google Search or uploaded documents.
Environment
op run --env-file .env.climbhill -- python .agents/skills/deep-research-gemini/scripts/gemini_research.py \
--prompt "Research current deep research APIs. Keep the answer concise and cite sources." \
--mode grounded \
--model gemini-3.5-flash
Required 1Password-backed variables:
GOOGLE_API_KEYGOOGLE_CLOUD_PROJECTwhen project-scoped Gemini or Google Cloud APIs need a project resource name
Cost Controls
- Use search grounding or Deep Research Agent only when fresh web/document research is required.
- Cap prompt scope and request concise reports.
- For benchmark parity, record whether the run used the Deep Research Agent, generateContent with grounding, or a manual two-step retrieval workflow.
- The benchmark command uses grounded Interactions API mode by default because
Gemini Deep Research Agent tasks are documented as agentic workflows that can
cost around or above the repository's
$1per-call budget. Use--mode deep-research-startonly for a deliberate live Deep Research Agent experiment.
Current Source Links
- https://ai.google.dev/gemini-api/docs/interactions/deep-research
- https://ai.google.dev/gemini-api/docs/google-search
- https://gemini.google/overview/deep-research/