Open-source companion to a technical book that teaches how to design, evaluate and ship LLM-based AI agents — includes the full Chinese manuscript, community translations, chapter-aligned runnable example projects, and reproducible evaluation harnesses.
Eight example apps for building with the Claude Agent SDK: an IMAP email assistant, a multi-agent research system, an Excel agent, a React/WebSocket chat UI, a .docx resume generator, and hello-world session demos. Local-only, not production.
Declares and installs agent dependencies from an apm.yml manifest—skills, prompts, agents, plugins and MCP servers—with transitive resolution, security auditing, plugin packaging, and cross-host registries so agents are reproducible across repos.
Embeds a GUI agent in your web page as client-side JavaScript, letting users drive the interface with natural language — it reads the DOM as text (no screenshots) and performs clicks and form fills. Bring your own LLM; no extension or backend required.
Enforces a brainstorm → plan → test-driven → review workflow on AI coding agents instead of letting them jump straight to code. Ships as composable skills that auto-trigger by context and run across Claude Code, Cursor, Copilot CLI, Gemini and more.
Autonomously performs end-to-end data science tasks — from cleaning and exploration to modeling, visualization, and analyst-grade reports — via an agentic LLM. Open-source model, code, datasets and demos; supports vLLM deployment, Jupyter/CLI/Web UIs, and OpenAI-style APIs.
Provides a persistent, dependency-aware structured memory for coding agents — replacing scattered markdown plans with a versioned task/issue graph backed by Dolt. Agent-optimized features include JSON output, dependency tracking, zero-conflict IDs, and semantic compaction for long-horizon workflows.
Provides a set of Claude Code skills that let an LLM-driven agent control Browserbase via browser automation and the official bb CLI — includes browser automation with anti-bot/solver support, cookie sync, fetch/tracing, site-debugging, and serverless function workflows.
A library of 232 ready-made AI agent personas across 16 divisions — engineering, design, marketing, sales, security, finance, and more. Each defines a role, workflow, and concrete deliverables rather than just a prompt template.
Decomposes a financial question into a research plan, then autonomously pulls live market data — income statements, balance sheets, cash flows — and self-checks until confident. Logs every tool call and reasoning step to JSONL scratchpads.
Provides a unified integration layer that lets AI agents call and manage third‑party service APIs while keeping credentials and approval workflows out of the agent's reach. Offers plugin-based integrations, per-tenant envelope encryption (KEK), configurable permission modes, and an optional Hub to host OAuth/webhook surfaces.
Terminal-based coding agent that reads and edits code, runs shell commands, and fetches web pages while planning multi-step tasks autonomously. A Ctrl-X toggle drops into a raw shell, and ACP support plugs it into Zed and JetBrains IDEs.