gemini-deep-research

Automating a literature review across multiple sources requires orchestrating a deep research agent to gather and synthesize findings. This Skill coordinates the Gemini Deep Research Agent to perform long-running web searches and generate structured reports with citations.

Yes, you can run long-running market analysis tasks using Python 3.8+ with the requests library. This Skill orchestrates the Gemini Deep Research Agent via a local Python runtime to perform complex competitive landscape studies and synthesize multi-source data.

To generate structured research reports with citations, you need Gemini API access, Python 3.8+ with the requests library, and a local runtime. The Skill orchestrates deep research tasks to produce comprehensive documentation with evidence from multiple sources.

Multi-source synthesis works effectively for technical deep dives and competitive analyses. This Skill coordinates the Gemini Deep Research Agent to gather information across various sources, applying structured reporting to document comprehensive technical and market findings.

Deep research orchestration handles complex multi-source syntheses by coordinating the Gemini Deep Research Agent to perform long-running web searches. It gathers, synthesizes, and documents comprehensive findings into structured reports with evidence and citations.

Limitations when running a deep research agent locally include requiring a runtime capable of handling long-running tasks without timing out. Users must provide their own Gemini API access and ensure the Python environment has the necessary requests library installed.