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Self-Improving Agent (Anti-Loop Hardened)
作者
_silhouette
· GitHub ↗
· v2.0.0
· MIT-0
297
总下载
0
收藏
1
当前安装
1
版本数
在 OpenClaw 中安装
/install self-improving-agent-hardened
功能描述
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User explicitly co...
安全使用建议
This skill appears coherent and implements what it claims: it logs learnings/errors into workspace files and provides safe guardrails to avoid feedback loops. Before installing or enabling hooks globally, review the provided scripts (activator.sh, error-detector.sh, extract-skill.sh) to confirm you’re comfortable with them running automatically in your environment. Prefer project-level hook configuration rather than user-global hooks if you want to limit how often these scripts run. Confirm the .learnings directory location and file permissions, and note that the scripts expect OpenClaw/Claude hook context (e.g., CLAUDE_TOOL_OUTPUT). If you need tighter control, keep the skill installed but only run it manually or enable hooks with restrictive matchers so it doesn't trigger on every prompt or tool use.
功能分析
Type: OpenClaw Skill
Name: self-improving-agent-hardened
Version: 2.0.0
The skill bundle is a framework for an AI agent to log errors, user corrections, and feature requests into markdown files for continuous improvement. It includes safety-focused 'Anti-Loop Guardrails' in SKILL.md to prevent recursive tool-use and token exhaustion, and the shell scripts (like extract-skill.sh) contain basic path-traversal protections to ensure file operations remain within the workspace. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found.
能力评估
Purpose & Capability
Name/description match what the files do: capture learnings/errors and append them to .learnings/*.md. Included scripts and hook handlers support that purpose (injecting bootstrap reminders, detecting command errors, scaffolding extracted skills). No unrelated credentials, binaries, or remote downloads are required.
Instruction Scope
SKILL.md instructs the agent to append entries to workspace files (.learnings/{LEARNINGS,ERRORS,FEATURE_REQUESTS}.md) and enforces tight guardrails (one learning per user message, max 3 tool calls, no chaining, cooldown). That scope is appropriate. Note: various reference docs describe OpenClaw APIs (sessions_list/history/send/spawn) and configuring hooks; those are advisory but could expand agent behavior if users adopt them. The skill itself does not automatically read/write unrelated system files or request secrets.
Install Mechanism
No remote install downloads or package installs are declared — this is an instruction-and-script bundle. The included shell scripts and hook handlers are local files that would be copied into the user's skills/hooks directories when installed. No extract-from-remote URLs or archives are used.
Credentials
The skill declares no required env vars or credentials. The hook scripts reference CLAUDE_TOOL_OUTPUT (expected in the hook context) and event/context objects provided by OpenClaw; these are reasonable and proportionate to detecting errors and injecting bootstrap reminders. No secrets or unrelated env vars are requested.
Persistence & Privilege
always:false (default), and the skill is user-invocable. However, the documentation encourages installing hooks (activator/error-detector) at project or user level; enabling user-level hooks means the scripts will run automatically with the agent's permissions whenever those events fire. This is normal for hooks but is a persistence/automation point the user should deliberate before enabling globally.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install self-improving-agent-hardened - 安装完成后，直接呼叫该 Skill 的名称或使用
/self-improving-agent-hardened触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v2.0.0
Anti-loop hardened fork: fixed infinite tool call loop vulnerability. Added guardrails: max 1 learning per message, max 3 tool calls, cooldown.
元数据
常见问题
Self-Improving Agent (Anti-Loop Hardened) 是什么？
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User explicitly co... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 297 次。
如何安装 Self-Improving Agent (Anti-Loop Hardened)？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install self-improving-agent-hardened」即可一键安装，无需额外配置。
Self-Improving Agent (Anti-Loop Hardened) 是免费的吗？
是的，Self-Improving Agent (Anti-Loop Hardened) 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Self-Improving Agent (Anti-Loop Hardened) 支持哪些平台？
Self-Improving Agent (Anti-Loop Hardened) 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Self-Improving Agent (Anti-Loop Hardened)？
由 _silhouette（@lanyasheng）开发并维护，当前版本 v2.0.0。
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