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Client-side meander.plan SDK: transport setup + a form-checked plan onto a real OTel span, with thin Claude/OpenAI bindings. Imports meander NOT.

A team of specialized AI agents (coordinator, security, frontend, accessibility, performance, QA) for web development, installable and updatable in any project via CLI.

The open, model-agnostic platform to build your own AI agent and run it everywhere — self-hosted, safe by default.

A tiny CLI for delegating bounded agent tasks to Cursor, Droid, OpenAI Codex, Claude Code, Grok Build, or Kimi Code runtimes.

Find out whether your AI agent's evals are lying to you: stability reports with flip attribution, LLM judge audits, and deterministic checks mined from your KB.

LLM-native React framework for deterministic UI generation. Data-driven by default, schema-driven optional. Ultra-low token consumption — built for AI agents, not just humans.

Kakunin compliance tools for LangChain JS/TS — verify agent certificates and scopes inside tools and chains

Maqam is an MIT-licensed agent framework for governed workflows, policy, evidence, skills, CLI workers, and crawler-backed research.

A 100% local, offline observer and devtools dashboard for AI agents and LLM applications.

TypeScript SDK for AI agents to take and repay revenue-underwritten credit on TrustLine (Stellar). Settles in USDC.

Predictive scheduling for autonomous LLM agents: suspend gracefully before rate limits, resume without losing work.

AI-Agent-One infrastructure agent CLI.

Тонкий шар роботи з LLM (локальні omlx + хмарні провайдери) поверх pi: model tiers, one-shot, agentic-раннери, write-guard, trace, telemetry, prompt-budget

Zero-trust repo intake for AI coding agents: scan the instruction environment before Claude Code, Cursor, Codex, or Gemini touches a repo.

Agentic Platform configuration domain package

`@agentic-ui-experience/ui-core` 提供生成和处理声明式 UI message 所需的基础能力：

`@agentic-ui-experience/ui-runtime` 的 React 适配器。

Drafted — visual thinking surface for humans and AI agents. Renders HTML, markdown, images, and code as frames on a zoomable canvas, with MCP tools for AI agents and real-time sync for humans.

Multi-agent stock & crypto screening with leakage-aware (point-in-time) LLM evaluation and an honest, mechanical backtest.

Deterministic workflow topology enforcement for LLM-powered systems.