andrewyng/context-hubPublic

AI summary: A centralized CLI registry providing curated, versioned documentation designed specifically for coding agents.

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JavaScriptMITCreated Oct 30, 2025Last push 2mo agoLatest release v0.1.4+23 stars this week+30 this month

Star history

since Mar 1, 2026
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13.9K stars as of Aug 7, 2026, tracked back to Mar 1, 2026. Historical curve reconstructed from public GitHub event archives, calibrated to the current total.

Contribution activity

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234 commits in the last yearLessMore

Signals and awards

derived from tracked data
  • Widely adopted

    13,899 stars

  • Outside contributions

    99% of recent commits from the community

  • Well documented

    High community health score

  • Permissive license

    MIT

  • Repeat trending

    4 trending appearances

What context-hub does

Context Hub acts as a repository of knowledge tailored for AI coding agents to prevent API hallucination and memory loss across sessions. It provides curated, versioned markdown documentation that agents can fetch on-demand using CLI commands. The system enables agents to attach persistent local annotations to these documents, allowing them to learn from past experiences and mistakes. Maintained entirely as open markdown in the repository, it ensures transparency so developers can inspect exactly what their agents are reading.

Context Hub is designed to be used by AI coding agents rather than humans, though developers orchestrating these agents will find it essential. It requires a Node.js environment to install the CLI tool.

  • Agent-Centric Documentation: Delivers API docs specifically formatted for LLM comprehension rather than human reading.
  • Versioned Knowledge Fetching: Allows agents to request specific versions of documentation for different languages or frameworks.
  • Persistent Local Annotations: Enables agents to attach notes to documents that persist across sessions for self-improvement.
  • Transparent Markdown Storage: Maintains all content as open markdown, allowing developers to inspect and audit agent knowledge.
  • Feedback Mechanisms: Allows agents to upvote or downvote documentation, sending signals directly to maintainers.
  • CLI-Driven Interaction: Provides a terminal interface (`chub`) designed explicitly for autonomous agent execution.

Where teams use it

Preventing API hallucinations

Developers can instruct their agents to query Context Hub for exact API schemas rather than relying on outdated pre-training data.

Cross-session learning

Agents can leave annotations about tricky edge cases in a framework, which are automatically retrieved in future sessions.

Framework migration assistance

Teams migrating to new library versions can provide their agents with exact, version-specific documentation via the CLI.

Skill bootstrapping

Users can prompt their agents to dynamically fetch the knowledge required to complete a task they haven't encountered before.

Getting started: npm install -g @aisuite/chub

README

main branch

Context Hub

Coding agents hallucinate APIs and forget what they learn in a session. Context Hub gives them curated, versioned docs, plus the ability to get smarter with every task. All content is open and maintained as markdown in this repo — you can inspect exactly what your agent reads, and contribute back.

MIT License npm Node.js

Quick Start

npm install -g @aisuite/chub
chub search openai                 # find what's available
chub get openai/chat --lang py     # fetch current docs (Python version) 

How It Works

Chub is designed for your coding agent to use (not for you to use!). You can prompt your agent to use 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 by creating an agent skill to use Chub using SKILL.md, and ideally prompting your agent to remember to use this skill. (If you are using Claude Code, create the directory ~/.claude/skills/get-api-docs and put SKILL.md there.)

Most of the time, it's simple — search, fetch, use:

chub search "stripe payments"        # find relevant docs
chub get stripe/api --lang js        # fetch the doc
# Agent reads the doc, writes correct code. Done.

When the agent discovers a gap, it can annotate locally for next time:

chub annotate stripe/api "Needs raw body for webhook verification"

# Next session, chub get notes that an annotation exists. Pass --with-annotations
# to include it — annotations are treated as untrusted input by default.

Feedback flows back to authorschub feedback stripe/api up or down — vote the docs up or down so they can get better for everyone over time.

Content Types

Versioned, language-specific. "What to know."

chub get openai/chat --lang py       # Python variant
chub get openai/chat --lang js       # JavaScript variant

More content types than API documentation (such as agent skills) are on the roadmap.

Commands

Command Purpose
chub search [query] Search docs and skills (no query = list all)
chub get <id> [--lang py|js] Fetch docs or skills by ID
chub annotate <id> <note> Attach a note to a doc or skill
chub annotate <id> --clear Remove annotations
chub annotate --list List all annotations
chub feedback <id> <up|down> Upvote or downvote a doc (sent to maintainers)

For the full list of commands, flags, and piping patterns, see the CLI Reference.

Self-Improving Agents

Context Hub is designed for a loop where agents get better over time.

Annotations are local notes that agents attach to docs. They persist across sessions and can be included on future fetches with --with-annotations — so agents can learn from past experience while treating prior notes as untrusted input. See Feedback and Annotations.

Feedback (up/down ratings with optional labels) goes to doc authors, who update the content based on what's working and what isn't. The docs get better for everyone — not just your local annotations.

  Without Context Hub                          With Context Hub
  ───────────────────                          ─────────────────
  Search the web                               Fetch curated docs
  Noisy results                                Higher chance of code working
  Code breaks                                  Agent notes any gaps/workarounds
  Effort in fixing                             ↗ Even smarter next session
  Knowledge forgotten
  ↻ Repeat next session

Key Features

Incremental Fetch

Docs can have multiple reference files beyond the main entry point. Fetch only what you need — no wasted tokens. Use --file to grab specific references, or --full for everything. See the CLI Reference.

Annotations & Feedback

Annotations are local notes that agents attach to docs — they persist across sessions and can be re-injected on future fetches with --with-annotations (off by default; the contents are treated as untrusted input). Feedback (up/down ratings) goes to doc authors to improve the content for everyone. See Feedback and Annotations.

Contributing

Anyone can contribute docs and skills — API providers, framework authors, and the community. Content is plain markdown with YAML frontmatter, submitted as pull requests. See the Content Guide for the format and structure.

Agent feedback (up/down ratings from real usage) flows back to authors, helping surface what needs fixing and improving overall quality over time.

License

MIT

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Recent activity

commits and pull requests

Recent open issues

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Releases and announcements

1 total
  1. v0.1.4v0.1.4Apr 27, 2026

    Bump version to 0.1.4

Commits per week

last 52 weeks
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234 commits in the last 52 weeks.

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Commit volume by weekday and hour (UTC). Larger dots mean more commits.

Who is committing

last 52 weeks
Maintainer commits3 (1%)
Community commits328 (99%)

331 commits in total over the last year.

DateListRankStars gained
Mar 17, 2026daily#11+294
Mar 12, 2026daily#17+202
Mar 11, 2026daily#15+164
Mar 10, 2026daily#5+348
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