
Agent Skills implementation for Strands Agents SDK

Agent Skills implementation for Strands Agents SDK
[ICML 2026] Meta Context Engineering via Agentic Skill Evolution
The first open-source agent skills builder. Define skills by vibe workflow, run on Claude Code, Cursor, Codex & more. Build Clawdbot 🦞· APIs for Lovable · Bots for Slack & Lark/Feishu · Skills are infrastructure, not prompts.
An enterprise AI development framework for building AI agents. It provides unified management of multi-provider LLMs, secure enterprise knowledge bases with high-precision retrieval, visual workflow orchestration and multi-agent coordination. Compatible with mainstream Agent Skill standards, it enables developers to efficiently build production-gra
Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI agents, data scientists and analysts build, validate, and cross-check product analytics, quantitative UX, customer journeys, graph-based user flows, behavioral segmentation, A/B tests, process mining models, Markov chain simulation
SkillOpt is a text-space optimizer that trains reusable natural-language skills for frozen LLM agents through trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts.
Markdown that runs — one file, any agent.
AtlasClaw is an enterprise agent framework supporting mutliple users and multi system integration.
Open-source customer money path for usage-based SaaS — authorize customer spend before paid work runs.

Real time communication for agents. Wake on message, channels, DMs and actions. Useful for orchestrating agents.
Interactive documents from Markdown. Extends MD with forms, approvals, webhooks, and more — built for next gen apps
AI agents and Nix: parametrable skills/instructions and tools, packaged together in a reproducible and modular fashion
Persistent Claude Code agents with scheduling, sessions, memory, and Telegram.
A selective learning and memory substrate for agentic systems — typed, revisable, decayable memory with competence learning and trust-aware retrieval.