gpt-researcher
Run the GPT Researcher autonomous agent to generate comprehensive deep research reports. Requires LLM and Search API keys (e.g., OPENAI_API_KEY, TAVILY_API_KEY).
Best use case
gpt-researcher is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Run the GPT Researcher autonomous agent to generate comprehensive deep research reports. Requires LLM and Search API keys (e.g., OPENAI_API_KEY, TAVILY_API_KEY).
Teams using gpt-researcher should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/gpt-researcher/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How gpt-researcher Compares
| Feature / Agent | gpt-researcher | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Run the GPT Researcher autonomous agent to generate comprehensive deep research reports. Requires LLM and Search API keys (e.g., OPENAI_API_KEY, TAVILY_API_KEY).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GPT Researcher Skill
This skill allows you to utilize the GPT Researcher Python package as an autonomous research agent.
## Setup
1. **Dependencies:** Requires `gpt-researcher` and its dependencies.
```bash
pip install gpt-researcher python-dotenv
```
2. **Configuration:** GPT Researcher needs API keys for an LLM (e.g., OpenAI) and a Search Provider (Tavily is recommended).
```bash
# Prompt user for keys if not set (assuming OpenAI and Tavily)
if [ -z "$OPENAI_API_KEY" ] || [ -z "$TAVILY_API_KEY" ]; then
echo "GPT Researcher requires API keys."
read -p "Enter your OpenAI API key: " OAI_KEY
read -p "Enter your Tavily API key: " TAVILY_KEY
echo "OPENAI_API_KEY=$OAI_KEY" >> .env
echo "TAVILY_API_KEY=$TAVILY_KEY" >> .env
if [ -f .gitignore ] && ! grep -q ".env" .gitignore; then echo ".env" >> .gitignore; fi
echo "API keys saved to .env."
fi
```
## Usage
Use the `scripts/run_research.py` script to initiate a research task.
### Command
```bash
python3 scripts/run_research.py --query "<query>" [--report-type <type>]
```
### Parameters
* `--query` (Required): The topic to research.
* `--report-type` (Optional): Default `research_report`. Options include: `research_report`, `resource_report`, `outline_report`, `deep_research_report`.
### Example
```bash
python3 scripts/run_research.py --query "The future of renewable energy sources" --report-type deep_research_report
```
## Output
The script outputs the final report in Markdown format to stdout. The research process (which can take several minutes) is logged to stderr.Related Skills
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