Provides an MCP server exposing 30+ trading tools — real-time prices, technical indicators, Bollinger Band scores, Reddit/news sentiment, and backtesting — designed to integrate with Claude/OpenClaw agents for automated market analysis.
Framework for building multi-modal AI agents that watch, listen, and reason over live video, pairing vision models (YOLO, Roboflow, Moondream) with LLMs like Gemini and OpenAI. Agents join calls in ~500ms and keep audio/video latency under 30ms.
Write repository automation as natural-language markdown that compiles into deterministic GitHub Actions workflows running AI agents. Agents run read-only by default and write only via sanitized safe-outputs. Works with Copilot, Claude, Codex, or Gemini.
Wraps the OpenCode CLI with a plan-first workflow: agents propose a plan you approve before any code is written, and a ContextScout step loads your repo's existing patterns so output matches house style, not generic boilerplate.
Defines a predictable repository-level instruction file for coding agents, giving teams one place to document workflow rules instead of each tool inventing its own context format.
Makes the spec an executable artifact: you write intent in structured markdown and AI agents generate the plan, task breakdown, and code from it. A specify CLI and slash commands drive a constitution-plan-tasks-implement workflow across 30+ coding agents.
Benchmark dataset for evaluating agents on long-horizon software-engineering tasks (repo-level patches, test-driven fixes). Includes golden patches, related tests, and problem statements in parquet format; aimed at agent debugging and code-modification evaluation but requires full test environments.
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.