langchain-deep-research
Run LangChain Open Deep Research agent for iterative web research and comprehensive reports. Requires LLM API keys and search API (e.g., OPENAI_API_KEY, TAVILY_API_KEY).
npx skills add majiayu000/claude-skill-registry --skill langchain-deep-research-closedloop-technolog-awesome-deep-resear --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LangChain Open Deep Research Skill This skill utilizes the LangChain Open Deep Research framework to perform iterative web research with reflection and knowledge gap identification, producing comprehensive reports with citations. ## Setup 1. **Dependencies:** Requires the `open-deep-research` package and LangGraph. ```bash pip install open-deep-research langgraph-cli python-dotenv ``` 2. **API Key Configuration:** Requires API keys for an LLM and a search provider. ```bash # Set up your API keys echo "# LLM Configuration" >> .env echo "OPENAI_API_KEY=your_openai_key" >> .env echo "# Search Configuration" >> .env echo "TAVILY_API_KEY=your_tavily_key" >> .env if [ -f .gitignore ] && ! grep -q ".env" .gitignore; then echo ".env" >> .gitignore; fi echo "API keys saved to .env." ``` ## Usage Use the `scripts/research.py` script to run a research task. ### Command ```bash python3 scripts/research.py --query "<research_query>" [--max-iterations <N>] ``` ### Parameters * `--query` (Required): The research question or topic. * `--max-iterations` (Optional): Maximum number of research iterations (default: 3). * `--output` (Optional): Output file path for the final report (default: stdout).
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pip install open-deep-research langgraph-cli python-dotenv echo "# LLM Configuration" >> .env echo "OPENAI_API_KEY=your_openai_key" >> .env echo "# Search Configuration" >> .env echo "TAVILY_API_KEY=your_tavily_key" >> .env if [ -f .gitignore ] && ! grep -q ".env" .gitignore; then echo ".env" >> .gitignore; fi echo "API keys saved to .env." python3 scripts/research.py --query "<research_query>" [--max-iterations <N>] python3 scripts/research.py --query "What are the latest developments in quantum computing error correction?" --max-iterations 4 --output report.md
What does the langchain-deep-research skill do?
Run LangChain Open Deep Research agent for iterative web research and comprehensive reports. Requires LLM API keys and search API (e.g., OPENAI_API_KEY, TAVILY_API_KEY).
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill langchain-deep-research-closedloop-technolog-awesome-deep-resear --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.