openai-deep-research
Use OpenAI's Deep Research API (o3 / o4 models) to automate multi-step, citation-backed research workflows.
Best use case
openai-deep-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use OpenAI's Deep Research API (o3 / o4 models) to automate multi-step, citation-backed research workflows.
Teams using openai-deep-research 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/openai-deep-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How openai-deep-research Compares
| Feature / Agent | openai-deep-research | 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?
Use OpenAI's Deep Research API (o3 / o4 models) to automate multi-step, citation-backed research workflows.
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
# OpenAI Deep Research Skill
This skill wraps OpenAI's Deep Research API so you can launch autonomous research runs (using `o3-deep-research` or `o4-mini-deep-research`) directly from Claude Code.
## Setup
1. **Dependencies:** Install the OpenAI SDK.
```bash
pip install openai python-dotenv
```
2. **API Key Configuration:** Export your OpenAI API key.
```bash
echo "OPENAI_API_KEY=sk-..." >> .env
if [ -f .gitignore ] && ! grep -q ".env" .gitignore; then echo ".env" >> .gitignore; fi
```
The Deep Research endpoint requires access to the Early Access program. Ensure your account is enabled before calling the API.
## Usage
Use `scripts/run_deep_research.py` to start a research job and stream the final report to stdout.
### Command
```bash
python3 scripts/run_deep_research.py --prompt "<research_question>" [--model o4-mini-deep-research] [--effort medium] [--json]
```
### Parameters
* `--prompt` (Required): The investigation prompt.
* `--model` (Optional): `o4-mini-deep-research` (default) or `o3-deep-research`.
* `--effort` (Optional): Reasoning depth, one of `low`, `medium`, `high` (default `medium`).
* `--json` (Optional): Emit the full response payload as JSON instead of just the synthesized report.
* `--output` (Optional): Write the report to a file path.
### Example
```bash
python3 scripts/run_deep_research.py \
--prompt "Assess the projected market impact of solid state batteries by 2030" \
--model o3-deep-research \
--effort high \
--output reports/solid-state-batteries.md
```
## Output
The script prints the synthesized Deep Research report (with citations) to stdout or saves it to the specified file. When `--json` is provided, the entire response payload (including intermediate steps, citations, and metadata) is emitted.
## Features
* **True Deep Research:** Uses OpenAI's autonomous planning, browsing, and synthesis stack.
* **Configurable Effort:** Choose between faster runs (`o4-mini-deep-research`) or higher-quality runs (`o3-deep-research`).
* **Intermediate Visibility:** Optional JSON output exposes the tool traces and citations returned by the API.Related Skills
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