error-guard
System safety and control-plane skill that prevents agent deadlocks and freezes. Provides non-LLM control commands to inspect task state, flush message queues, cancel long-running work, and recover safely without restarting the container. Use when implementing or operating long-running tasks, sub-agents, benchmarks, background monitors (e.g., Moltbook, PNR checks), or when the system becomes unresponsive and needs immediate recovery controls.
Best use case
error-guard is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
System safety and control-plane skill that prevents agent deadlocks and freezes. Provides non-LLM control commands to inspect task state, flush message queues, cancel long-running work, and recover safely without restarting the container. Use when implementing or operating long-running tasks, sub-agents, benchmarks, background monitors (e.g., Moltbook, PNR checks), or when the system becomes unresponsive and needs immediate recovery controls.
Teams using error-guard should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/error-guard/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How error-guard Compares
| Feature / Agent | error-guard | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
System safety and control-plane skill that prevents agent deadlocks and freezes. Provides non-LLM control commands to inspect task state, flush message queues, cancel long-running work, and recover safely without restarting the container. Use when implementing or operating long-running tasks, sub-agents, benchmarks, background monitors (e.g., Moltbook, PNR checks), or when the system becomes unresponsive and needs immediate recovery controls.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# error-guard ⚠️ **System‑level skill (Advanced users)** This skill defines the **control‑plane safety primitives** for OpenClaw. It is intentionally minimal, non‑blocking, and designed to prevent agent freezes, deadlocks, and unrecoverable states when running long‑lived or high‑risk workloads. ## Design Principles > **Warning:** This skill operates at the agent control‑plane level. > It should be installed only by users who understand OpenClaw’s execution model and are running workloads that can block, hang, or run for extended periods. - **Main agent never blocks**: no long exec, no external I/O, no LLM calls. - **Event-driven**: workers emit events; the control plane listens. - **Fail-safe first**: recovery commands must always respond. - **Minimal state**: track only task metadata (never payloads). ## Command Surface (Phase 1) ### /status Report current system health and task registry state. Returns: - Active tasks (taskId, type, state) - Start time and last heartbeat - Flags for stalled or overdue tasks Constraints: - Must run in constant time - Must not call any model or external API ### /flush Emergency stop. Immediately: - Cancel all active tasks - Kill active exec/process sessions - Clear pending message queue - Reset in-memory task registry Constraints: - Must always respond - No waiting on workers - No model calls ### /recover Safe recovery sequence. Steps: 1. Execute `/flush` 2. Reset control-plane state 3. Optionally reload skills/state (no container restart) ## Future Extensions (Not Implemented Yet) - Sub-agent runner helper (event-driven) - Task watchdogs with TTL and silence detection - Structured event protocol (task.started, task.heartbeat, task.completed, ...) - Back-pressure and task classes (interactive / batch / background) ## Security & Privacy - This skill **does not** store payloads, prompts, messages, or model outputs - Only minimal task metadata is persisted (taskId, timestamps, state) - No API keys, credentials, or user data are read or written - Safe to publish and share publicly ## Non-Goals - No business logic - No background polling loops - No user-facing features - No LLM reasoning paths This skill is the **last line of defense**. Keep it small, fast, and reliable.
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龙虾安全卫士 (openclaw-safe-guard) v1.2.3
## 📦 来源信息