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OpenClaw Self-Improvement

作者 X-RayLuan · GitHub ↗ · v0.2.9 · MIT-0
cross-platform ⚠ suspicious
1700
总下载
0
收藏
10
当前安装
11
版本数
在 OpenClaw 中安装
/install openclaw-self-improvement
功能描述
A reusable operator-guided workflow improvement skill for OpenClaw and ClawLite that turns repeated failures into logged learnings, binary eval loops, SOPs,...
安全使用建议
This skill appears to do what it says: local logging, experiments, and promotion into local docs. Before installing or running it, confirm the workspace path it will use (WORKSPACE env var or default ~/.openclaw/workspace). Avoid setting WORKSPACE or OBSIDIAN_LEARNINGS_DIR to system-critical or sensitive directories (e.g., /, /etc, or project roots you don't want modified). Use promote-learning --dry-run to preview promotions; remember log-learning and log-experiment will append to files immediately. If you want extra safety, run the scripts in a dedicated, write-isolated directory or with a disposable user account to limit accidental modifications.
功能分析
Type: OpenClaw Skill Name: openclaw-self-improvement Version: 0.2.9 The skill provides a mechanism for an AI agent to modify its own core instruction and configuration files (AGENTS.md, TOOLS.md, SOUL.md) based on 'learnings' derived from its operations. While the scripts (e.g., scripts/promote-learning.mjs and scripts/log-learning.mjs) are simple file-appending utilities and the documentation emphasizes operator review, the design inherently enables persistent prompt injection. If an agent is tricked into 'learning' a malicious instruction and then 'promoting' it, the agent's future behavior could be permanently compromised. No evidence of intentional malice or data exfiltration was found, but the capability for self-modification of instructions is a high-risk pattern.
能力评估
Purpose & Capability
Name/description (self-improvement, logging, eval loops, promotion into AGENTS/TOOLS/SOUL/Obsidian) match the included scripts and references. The only required runtime is node, which the package.json and scripts expect. The write targets ('.learnings/', AGENTS.md, TOOLS.md, SOUL.md, optional Obsidian export) are coherent with promotion and logging behavior.
Instruction Scope
Runtime instructions are local-file operations and the scripts follow them: log-learning and log-experiment append structured blocks to files under WORKSPACE (or default ~/.openclaw/workspace). promote-learning echoes the resolved path and supports --dry-run before appending. experiment-summary reads EXPERIMENTS.md and outputs JSON. There is no network I/O or external endpoints. Note: the log scripts will append immediately (no dry-run) to whichever workspace path is resolved, so verify the workspace before running.
Install Mechanism
There is no install spec in the registry entry; the package contains small Node scripts and an npm-style package.json (private). No remote downloads or executable installers are used, lowering install risk. Typical usage is 'npm install' or running the scripts directly with node.
Credentials
The skill does not request secrets or external credentials. Scripts read optional environment variables WORKSPACE and OBSIDIAN_LEARNINGS_DIR (falling back to HOME/.openclaw/workspace). Registry metadata lists no required env vars — a minor mismatch with SKILL.md which documents those env vars. Because those vars control filesystem targets, operators should ensure they point at intended directories (not system or sensitive locations).
Persistence & Privilege
The skill is not always-enabled and does not modify other skills or global agent settings. It writes to local files under the resolved workspace/obsidian path only; promote-learning prints the path and supports --dry-run. Autonomous invocation is allowed by default (platform normal), but this skill's actions are limited to local file writes and reads.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install openclaw-self-improvement
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /openclaw-self-improvement 触发
  4. 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
v0.2.9
Align metadata and write-boundary declarations.
v0.2.8
Harden promotion paths and align docs.
v0.2.7
Update listing descriptions for SEO and GEO clarity.
v0.2.6
Sync SKILL.md summary with short multilingual description
v0.2.5
Shorten package description to avoid UI truncation while keeping multilingual cues
v0.2.4
Update package description with inline multilingual text for ClawHub listing
v0.2.3
Fix SKILL description formatting so multilingual text is rendered inline on directory listing
v0.2.2
Add multilingual SKILL description (EN/ZH/JA/KO/ES) for openclaw-self-improvement intro
v0.2.1
Safer packaging: workspace-local default exports, explicit local-only safety notes, removed embedded .git metadata.
v0.2.0
Add eval-loop support, decision rules, practical examples, experiment summary helper, and self-improvement daily routine integration.
v0.1.0
Initial self-improvement skill with learnings logs, promotion flow, and Obsidian support.
元数据
Slug openclaw-self-improvement
版本 0.2.9
许可证 MIT-0
累计安装 12
当前安装数 10
历史版本数 11
常见问题

OpenClaw Self-Improvement 是什么?

A reusable operator-guided workflow improvement skill for OpenClaw and ClawLite that turns repeated failures into logged learnings, binary eval loops, SOPs,... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1700 次。

如何安装 OpenClaw Self-Improvement?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install openclaw-self-improvement」即可一键安装,无需额外配置。

OpenClaw Self-Improvement 是免费的吗?

是的,OpenClaw Self-Improvement 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

OpenClaw Self-Improvement 支持哪些平台?

OpenClaw Self-Improvement 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 OpenClaw Self-Improvement?

由 X-RayLuan(@x-rayluan)开发并维护,当前版本 v0.2.9。

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