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/deep-research

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

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master-skills
12200 skills
Install
$ npx -y skills add sinhoneyy/master-skills --skill deep-research --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/deep-research

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

deep-research.SKILL.md
name: deep-research
description: "Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports."
risk: safe
source: "https://github.com/sanjay3290/ai-skills/tree/main/skills/deep-research"
date_added: "2026-02-27"

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:

   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)

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Read more
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