I built a static analysis tool that audits LangChain agents for excess tool permissions before they ship. Here's what it found on typical agent patterns developers use every day.
When you write this:
agent = initialize_agent(
tools=[GitHubTool, SlackTool, SQLDatabaseTool],
llm=llm,
agent_kwargs={"system_message": "You summarize pull requests."}
One of the fastest ways for LangChain agents to become unstable in production is not model...
CLI-Anything generates SKILL.md files that AI agents trust and execute. Snyk found 13.4% of agent skills contain critical…
🙋 I’m Luhui Dev, a developer who has been breaking down Agent engineering and exploring how AI can...
AI agents choose tools from shared registries by matching natural-language descriptions. But no human is verifying whether those…
Your agent does whatever it reasoned it should do. Sometimes that means finishing the task. Sometimes...
I built my first agent last night using the Anthropic Python SDK directly. No LangChain, no CrewAI,...
