deep-research

Data, Backend & API

"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 minutes but produces detailed, cited reports. Costs $2-5 per task."

Documentation

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](https://aistudio.google.com/)
2.Set the environment variable:

```bash

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)

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