Self-hosted control plane for AI agents: dispatch tasks, review runs, track spend, and operate OpenClaw, Claude Code, Codex, and other runtimes.
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Updated
Sep 14, 2026 - TypeScript
Self-hosted control plane for AI agents: dispatch tasks, review runs, track spend, and operate OpenClaw, Claude Code, Codex, and other runtimes.
Public, source-cited Fable 5, Mythos, Claude Code, and agent-operations second brain. Not affiliated with Anthropic.
AI-assisted setup kit for testing a low-cost open-model orchestrator/executor stack.
🖥️ SATO OS — Onchain Agent Mission Control. Build and run your onchain agent on any chain, using any model.
给AI当老板 — 21章AI Agent团队搭建实战手册 / Managing AI Agents: The Complete Playbook (Bilingual)
Astromesh Leia — Claude Code plugin for agent operations in plain English: create, deploy and monitor WhatsApp and multi-channel agents on Astromesh Nexus without touching Kubernetes.
Free starter kit for running AI coding agents with proof gates, status badges, and lane discipline. MIT.
Sample-first AI secretary proof for mailbox triage, draft-only replies, and human confirmation queues.
Portable agent operations kit for durable, verifiable work across coding-agent harnesses.
Claude Code / AIエージェントの運用統制ハンドブック — field-tested governance patterns for AI agents: work packets, independent replay, multiplicity ledgers, kill logs, fail-closed gates
Local operational dashboard and guarded admin cockpit for OpenClaw
Decision gate that stops AI agents from burning tokens on subagents that can't deliver
Practical baseline for running AI agents on-prem. Checklists, safe defaults, and operator field notes for local-first deployments.
A written doctrine for running a fleet of AI agents under real operational discipline: budgets, verification gates, contract templates, and a failure ledger.
AI agent operations control plane for agent registry, tool governance, knowledge tracking, run monitoring, and audit evidence.
Accessible, evidence-driven governance and requirements foundation for an Agent Operations Cockpit in C#/.NET
Battle-tested ops patterns for running AI agents in production — post-change audit, self-healing watchdogs, provider fallback, model routing diagnostics, WeChat message rules, and more.
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