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Self Improving Agent
作者
chengyz3327-design
· GitHub ↗
· v3.0.7
· MIT-0
139
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install warren-self-improving-agent-v2
功能描述
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
安全使用建议
This skill is coherent with its stated goal of logging and promoting learnings and appears safe to inspect and opt into, but take these precautions before enabling it globally: 1) Review the hook handler (hooks/openclaw/handler.{js,ts}) and the scripts (scripts/activator.sh, error-detector.sh, extract-skill.sh) so you understand what will run and when. 2) Note that enabling hooks writes or references files under your ~/.openclaw (or project) workspace and will inject reminder content into sessions — enable only if you use OpenClaw/Claude-style hooks. 3) The error detector reads CLAUDE_TOOL_OUTPUT (tool output); ensure you’re comfortable with hooks inspecting tool outputs in your environment. 4) If you enable scripts, prefer project-level (not global) configuration for testing; test with dry-run / minimal setup first. 5) The extract-skill.sh includes path checks preventing absolute/parent directory writes, but avoid running it with elevated privileges and verify generated files before promoting them. If you don’t use OpenClaw or hooks, you can still use the logging templates manually without installing hooks.
功能分析
Type: OpenClaw Skill
Name: warren-self-improving-agent-v2
Version: 3.0.7
The 'self-improving-agent' skill bundle is designed to help AI agents log errors, user corrections, and best practices into a local `.learnings/` directory for continuous improvement. It includes utility scripts like `extract-skill.sh` for scaffolding new skills from logs and `error-detector.sh` for identifying command failures via environment variables. The OpenClaw hooks (`handler.js`, `handler.ts`) and markdown instructions (`SKILL.md`) are strictly aligned with the stated purpose of self-documentation and workflow optimization, showing no signs of data exfiltration, unauthorized persistence, or malicious prompt injection.
能力评估
Purpose & Capability
The name/description describe logging learnings and promoting them into workspace files; the repository contains templates, logging formats, helper scripts, and an OpenClaw hook that injects reminders. Required binaries/env/credentials are none, which matches a local logging/promote workflow. The provided scripts and hook directly support the described functionality (activator, error detector, extract-skill), so the requested capabilities are proportionate to the stated purpose.
Instruction Scope
The SKILL.md instructs copying hooks into ~/.openclaw/hooks, creating ~/.openclaw/workspace/.learnings (or project-level .learnings/), and optionally enabling hooks that run on lifecycle events. The scripts read the CLAUDE_TOOL_OUTPUT environment variable (used by PostToolUse hooks) and output reminder blocks; extract-skill.sh creates new skill directories. These instructions stay within the scope of capturing and scaffolding learnings, but they do give the skill a way to inject content into every session (via workspace files and hook injection). Review the hook handler and scripts before enabling to ensure you’re comfortable with that session-level injection.
Install Mechanism
There is no network-based install spec; this is an instruction-first skill with bundled scripts and hooks. That is lower-risk than remote downloads. The included extract-skill.sh writes files but contains path checks that prevent absolute paths and parent-directory writes. The hook handler only inserts a virtual bootstrap file and does not perform network requests. Overall install mechanism is proportional and localized.
Credentials
The skill declares no required environment variables or credentials, which is appropriate. However, the error-detector script reads CLAUDE_TOOL_OUTPUT (an environment variable provided by the host agent runtime). This is expected for a PostToolUse hook but is an environment access worth noting: the hook can inspect tool output text. No secrets (API keys, AWS, tokens) are requested or required by the skill.
Persistence & Privilege
always:false (no forced/global inclusion). The skill instructs users to copy hooks and workspace files into their OpenClaw home (e.g., ~/.openclaw/), which, if enabled, gives it recurring presence and the ability to inject reminders into each session. This is expected for a self-improvement hook, but you should treat enabling hooks as granting ongoing influence over session context (opt-in rather than automatic).
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 warren-self-improving-agent-v2 - 安装完成后,直接呼叫该 Skill 的名称或使用
/warren-self-improving-agent-v2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
v3.0.7
- Major documentation overhaul for v3.0.7: detailed skill usage instructions, new logging standards, and project integration guidelines.
- Expanded "Quick Reference" with use-case-specific logging guidance.
- Added comprehensive setup instructions for OpenClaw and generic agent workflows.
- Standardized formats for logging learnings, errors, and feature requests in markdown.
- Included procedures for promoting important learnings to long-term project memory files.
- Clarified workspace structure and support for inter-session communication in OpenClaw.
元数据
常见问题
Self Improving Agent 是什么?
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 139 次。
如何安装 Self Improving Agent?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install warren-self-improving-agent-v2」即可一键安装,无需额外配置。
Self Improving Agent 是免费的吗?
是的,Self Improving Agent 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Self Improving Agent 支持哪些平台?
Self Improving Agent 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?
由 chengyz3327-design(@chengyz3327-design)开发并维护,当前版本 v3.0.7。
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