Gemini Deep Research

OrganizationPopular

OpenLAIR

gemini-deep-research

Perform deep, multi-source research using Google Gemini's Deep Research Agent. Use this skill whenever the user asks for comprehensive research, literature reviews, competitive analysis, market research, technology surveys, or any investigation that requires synthesizing information from many web sources. Also trigger when the user says "deep research", "research this thoroughly", "do a comprehensive study on", or wants a structured report with evidence gathered from across the web — even if they don't mention Gemini by name.

Overview

Publisher	OpenLAIR
Repository	`dr-claw`
Skill name	`gemini-deep-research`
Stars	1.2K
Forks	136
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by OpenLAIR on GitHub. Read the source before you install it.

Installation

Install the Gemini Deep Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/OpenLAIR/dr-claw/tree/main/skills/gemini-deep-research
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/OpenLAIR/dr-claw.git /tmp/dr-claw
mkdir -p .claude/skills
cp -r /tmp/dr-claw/skills/gemini-deep-research .claude/skills/gemini-deep-research

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gemini Deep Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Gemini Deep Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Gemini Deep Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Gemini Deep Research

Google Gemini's Deep Research Agent autonomously breaks down complex queries, searches the web systematically, and produces structured markdown reports with citations. It handles the kind of multi-source synthesis that would take a human hours of browsing.

Prerequisites

GEMINI_API_KEY environment variable must be set (obtain from Google AI Studio)
Python 3.8+ with the requests library installed
Requires a direct Gemini API key — OAuth tokens are not supported

How to Run the Script

The script is at scripts/deep_research.py relative to this skill's directory (i.e., the directory containing this SKILL.md). Resolve the full path from the skill's location before running.

bash
python3 <this-skill-directory>/scripts/deep_research.py \
  --query "<research query>" \
  --stream \
  --output-dir ./reports

Key flags

Flag	Purpose	Default
`--query`	(required) The research question	—
`--stream`	Print progress updates while waiting	off
`--output-dir`	Where to save the report files	current dir
`--format`	Custom output structure (see example below)	free-form
`--file-search-store`	Gemini file-search store name	none
`--api-key`	Override `GEMINI_API_KEY` env var	env var

Before running

Check for GEMINI_API_KEY: Run echo $GEMINI_API_KEY to see if it's set. If empty, ask the user whether they'd like to provide a Gemini API key (they can get one from https://aistudio.google.com/apikey). If the user provides one, pass it via --api-key. If the user declines, do not use this skill — fall back to other research approaches and let the user know why.
Ensure requests is installed: python3 -c "import requests". If missing, install it: pip3 install requests.

Example commands

Basic research:

bash
python3 <this-skill-directory>/scripts/deep_research.py \
  --query "Current state of quantum error correction techniques" \
  --stream --output-dir ./reports

Custom output format:

bash
python3 <this-skill-directory>/scripts/deep_research.py \
  --query "Competitive landscape of EV batteries" \
  --format "1. Executive Summary\n2. Key Players (data table)\n3. Technology Comparison\n4. Supply Chain Risks" \
  --stream --output-dir ./reports

Output

The script produces two timestamped files in the output directory:

deep-research-YYYY-MM-DD-HH-MM-SS.md — the final markdown report
deep-research-YYYY-MM-DD-HH-MM-SS.json — full interaction metadata

The report is also printed to stdout so you can capture it directly.

Execution Notes

This is a long-running task — it typically takes 2–10 minutes depending on query complexity. Use --stream so the user can see progress.
Always run with a reasonable timeout (at least 600000ms / 10 minutes) when using the Bash tool.
After the script finishes, read and present the generated .md report to the user. Summarize key findings and point them to the full report file.

API Details

Endpoint: https://generativelanguage.googleapis.com/v1beta/interactions
Agent model: deep-research-pro-preview-12-2025
Auth: x-goog-api-key header

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

scripts/deep_research.py6 KB

Frequently asked questions

What does the Gemini Deep Research AI skill do?

Why use Gemini Deep Research on TypingMind?

Because you install it once and use it with any model. Gemini Deep Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Gemini Deep Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OpenLAIR/dr-claw/tree/main/skills/gemini-deep-research. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Gemini Deep Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Gemini Deep Research?

As many as you like. As long as a model supports skills, you can use Gemini Deep Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Gemini Deep Research AI skill free?

Yes. It is published on GitHub by OpenLAIR under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Gemini Deep Research

Prerequisites

How to Run the Script

Key flags

Before running

Example commands

Output

Execution Notes

API Details

Bundled files

Frequently asked questions

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