Skip to content

Preparing Archive

Advanced
5d 1h ago
Safe

deep-research

Execute autonomous multi-step research using Google Gemini Deep Research Agent. Use for: market analysis, competitive landscaping, literature reviews, technical research, due diligence. Takes 2-10 ...

.agents/skills/deep-research Python
PY
TY
BA
4+ layers Tracked stack
Capabilities
0
Signals
0
Related
3
0
Capabilities
Actionable behaviors documented in the skill body.
0
Phases
Operational steps available for guided execution.
0
References
Support files available for deeper usage and onboarding.
0
Scripts
Runnable or reusable automation artifacts discovered locally.

Architectural Overview

Skill Reading

"This module is grounded in ai engineering patterns and exposes 1 core capabilities across 1 execution phases."

Gemini Deep Research Skill

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

When to Use This Skill

Use this skill when:

  • Performing market analysis
  • Conducting competitive landscaping
  • Creating literature reviews
  • Doing technical research
  • Performing due diligence
  • Need detailed, cited research reports

Requirements

  • Python 3.8+
  • httpx: pip install -r requirements.txt
  • GEMINI_API_KEY environment variable

Setup

  1. Get a Gemini API key from Google AI Studio
  2. Set the environment variable:
    export GEMINI_API_KEY=your-api-key-here
    
    Or create a .env file in the skill directory.

Usage

Start a research task

python3 scripts/research.py --query "Research the history of Kubernetes"

With structured output format

python3 scripts/research.py --query "Compare Python web frameworks" \
  --format "1. Executive Summary\n2. Comparison Table\n3. Recommendations"

Stream progress in real-time

python3 scripts/research.py --query "Analyze EV battery market" --stream

Start without waiting

python3 scripts/research.py --query "Research topic" --no-wait

Check status of running research

python3 scripts/research.py --status <interaction_id>

Wait for completion

python3 scripts/research.py --wait <interaction_id>

Continue from previous research

python3 scripts/research.py --query "Elaborate on point 2" --continue <interaction_id>

List recent research

python3 scripts/research.py --list

Output Formats

  • Default: Human-readable markdown report
  • JSON (--json): Structured data for programmatic use
  • Raw (--raw): Unprocessed API response

Cost & Time

Metric Value
Time 2-10 minutes per task
Cost $2-5 per task (varies by complexity)
Token usage ~250k-900k input, ~60k-80k output

Best Use Cases

  • Market analysis and competitive landscaping
  • Technical literature reviews
  • Due diligence research
  • Historical research and timelines
  • Comparative analysis (frameworks, products, technologies)

Workflow

  1. User requests research → Run --query "..."
  2. Inform user of estimated time (2-10 minutes)
  3. Monitor with --stream or poll with --status
  4. Return formatted results
  5. Use --continue for follow-up questions

Exit Codes

  • 0: Success
  • 1: Error (API error, config issue, timeout)
  • 130: Cancelled by user (Ctrl+C)

Primary Stack

Python

Tooling Surface

Guide only

Workspace Path

.agents/skills/deep-research

Operational Ecosystem

The complete hardware and software toolchain required.

This skill is mostly documentation-driven and does not expose extra scripts, references, examples, or templates.

Module Topology

Skill File
Parsed metadata
Skills UI
Launch context
Chat Session
Antigravity Core

Antigravity Core

Principal Engineering Agent

A high-performance agentic architecture developed by Deepmind for autonomous coding tasks.
120 Installs
4.2 Reliability
1 Workspace Files
4.2
Workspace Reliability Avg
5
68%
4
22%
3
10%
2
0%
1
0%
No explicit validation signals were parsed for this skill yet, but the module remains available for inspection and chat launch.

Recommended for this workflow

Adjacent modules that complement this skill surface

Loading content
Cart