About This Site
Open-source runtime for safely running coding agents without constant supervision Agent AFK is an open-source, local-first runtime for running coding agents unattended. It allows developers to start coding tasks, walk away, and later review verified results through traces, terminal states, and receipts of agent activity. The runtime supports permission boundaries, reversibility gates, isolated worktrees, parallel subagents, adversarial verification, persistent session memory, and Telegram supervision. It works with Claude, Cursor, Claude Code, Codex, custom agents, and other model providers while keeping the runtime and data on the user's machine.
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Key Features AI
Core Features
Unattended coding-agent execution with daemon and background workflows
Permission boundaries, reversibility gates, isolated worktrees, and risk-aware actions
Parallel subagent orchestration with coordinated interruption
Adversarial verification and self-checking before changes are accepted
Complete local trace history for sessions, subagents, and tool calls
Explicit terminal states including Done, Blocked, Asking, and Interrupted
Telegram supervision for notifications, responses, redirection, and interruption
Composable slash skills such as /mint, /diagnose, /review, /shadow-verify, and /ship
Persistent plans, preferences, conventions, decisions, and session memory
Support for external and local model providers through a BYO-model approach
Advantages
Open-source and Apache-2.0 licensed
Free runtime with all core features included
No account required
Runs locally with support for macOS and Linux
Works with multiple model providers, including local models
Provides detailed traces and visible tool calls for accountability
Includes verification workflows instead of relying only on agent claims
Supports remote supervision through Telegram
Uses isolated worktrees and reversibility-aware controls to reduce blast radius
Persistent plans, memory, and recovery paths help manage long-running tasks
缺点：Requires Node.js 20 or newer and command-line setup
缺点：Currently positioned primarily for macOS and Linux users
缺点：Users must provide and pay for their own model usage
缺点：Configuring agents, Telegram, repositories, and custom workflows may require technical expertise
缺点：The paid support plans are expensive for individual developers
缺点：Autonomous coding still requires human review before risky changes are shipped
缺点：Performance and output quality depend partly on the selected model provider
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