Dear friends,
I’m thrilled to announce Context Hub, a new tool to give to your coding agents the API documentation they need to write correct code. If you’re building AI systems using modern technologies, your coding agent will often use outdated APIs, hallucinate parameters, or not even know about the tool it should be using. This happens because AI tools are rapidly evolving, and coding agents were trained on old data that does not reflect the latest tools. Context Hub, which is designed for your coding agent to use (not for you to use!) provides the context it needs. It also accepts automatic agentic feedback to help your coding agents improve over time.
For example, Claude Opus 4.6, possibly the best coding model currently, has a knowledge cutoff date of May 2025. When I ask it to write code to call OpenAI's GPT-5.2, it uses the older OpenAI chat completions API (client.chat.completions.create) rather than the newer responses API (client.responses.create) that OpenAI recommends. Even though the newer API is a year old, there's a lot more data that Opus was trained on that uses the older interface. It also has no idea about the existence of Nano Banana, which was released in August 2025. More generally, I’ve seen coding models fail to make correct API calls to Gemini and many database services (even popular ones, when I use less common parameter choices), or just not know about a particular tool I want.
Consequently, I’ve found myself often writing documentation in Markdown (with help from AI and web search) to give to my coding agent information on how to use different services. In lieu of every developer doing this manually for every service they want to use, over a weekend, Rohit Prsad and I got together to develop an open context management system for giving coding agents the context they need. I’m also grateful to Xin Ye and Neil Thomas for helping with this project.
I encourage you to install Context Hub (chub for short) using npm, and run it to get a sense of its output:
npm install -g @aisuite/chub
chub search openai # find what's available
chub get openai/chat --lang py # fetch current docs
To get your coding agent to use chub, either prompt it (e.g., "Use the CLI command chub to get the latest API documentation for calling OpenAI. Run 'chub help' to understand how it works."), or give it an agent skill to use chub automatically, by using SKILL.md, and ideally prompt your agent to remember to use it. (If you are using Claude Code, create the directory ~/.claude/skills/get-api-docs and put this file there).
Chub is built to enable agents to improve over time. For example, if an agent finds that the documentation for a tool is incomplete but discovers a workaround, it can save a note so as not to have to rediscover it from scratch next time.
Alongside the explosive growth of OpenClaw, we’ve seen the remarkable rise of the social network Moltbook for agents, where agents share information and debate with each other. Motivated by this, we plan to evolve chub toward letting different agents share information about what they discover about different tools and where documentation might contain bugs. This is not yet implemented, but it will be exciting to see a community of coding agents help each other!
We’ve populated chub with an initial set of documentation for some of the most popular tools, like common LLM providers, databases, payment processors, identity management solutions, messaging platforms, and so on. You can see the current list here. If you’re a provider of a popular agent tool, please consider contributing documentation. I hope our community can collectively improve Context Hub for everyone.
Keep building!
Andrew