#agents

PartyKit, for Workers

Sign and verify orchestrated HTTP requests

The deal-making layer for the agentic internet. An open standard for structured negotiation between autonomous agents.

Convert AI coding agent sessions (Claude Code, Cursor, Codex, Gemini, OpenCode, Kimi Code, Hermes) into self-contained, embeddable HTML replays

The form framework for coding agents

Hexabot v3 is an AI workflow automation platform, combining workflows, actions, agents, and conversational channels in one runtime.

Open-source agentic workspace enterprises can make their own. Connect the systems you already run — 100+ integrations, MCP, chat tools, apps, browser, local files — with shared memory. Any agent (Claude Code, Codex), any model, or BYOK. Set up in clicks, not months. Local-first: your data never leaves your machines.

A command-line tool that injects credentials to curl requests to known public APIs.

Ruby's capable AI runtime

Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.

Repository-native operating context and dynamic control for coding agents: continuity, reusable procedures and current constraints across sessions. Rust, Python and TypeScript.

Easily switch between alternative low-cost AI models in Claude Code/Agent SDK. For those comfortable using Claude agents and commands, it lets you take what you've created and deploy fully hosted agents for real business purposes. Use Claude Code to get the agent working, then deploy it in your favorite cloud.

Runtime governance for AI agents. Allow, warn, or block every model and tool call before it commits. Hash-chained audit for every decision. Compliance packs for SOC 2, HIPAA, PCI DSS, EU AI Act, SR 11-7, and FDA CSA. Apache 2.0.

Repo-native governance kernel for bounded, convergent, proof-backed agent work.

Flow Agentique Grimoire-kit

The harness interoperability layer for coding agent. Agent to Agent connect over ACP, A2A and UHP

The missing bridge between your ML models and your AI agents.

Fabricatio is a Python library designed for building applications that leverage Large Language Models (LLMs) using an event-based agent structure. It utilizes Handlebars for templating and provides a robust framework for managing tasks, workflows, and toolboxes, enabling developers to create intelligent and efficient applications.

Portable workflow patterns for Agents. Ships my learned best practices as a plugin so I don't have to re-teach them every session.

Neutral control plane for coding-agent fleets: claims, roles, mailbox reliability, receipts, audit, federation, dead-letter visibility, sandbox receipts, and cross-agent coordination. This is still pre-1.0.0 - Software works however you might need help from your local agents to set it up.

No repository description published.

Synthetic data curation for post-training and structured data extraction

Lights, Cameras, (GitHub) Actions!

Control plane for your harness across many repos — durable personas, per-task workspaces, and a credential vault the model never reads from

A declarative language for LLM-driven state machines - the .mkl document is the program, an LLM is the runtime

A sandboxed, full-featured agent operating system in a single Go binary. Bring any model, manage local models, point it at a goal, and grant it real authority: every action is sandboxed, governed, and sealed into a verifiable, tamper-evident record an independent party can check. Runs interactive or 24/7, or embed it in your own system.

Governance-grade, OKF-compatible knowledge-base format with a single-writer MCP server and CLI. Pre-release.

Universal memory runtime for AI agents

The why layer of repo-native project memory: the reasoning behind a codebase as Markdown in the repo, versioned by Git, for coding agents and humans, so nothing rejected is proposed twice. No database, no daemon, no account.

Intellectual property data tools for AI agents