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Xiaopi Self Improving

作者 Adin · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
97
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当前安装
1
版本数
在 OpenClaw 中安装
/install xiaopi-self-improving
功能描述
AI自我改进与记忆系统 - 解决'同类错误反复犯、用户纠正不长记性'的痛点。自动捕获错误、用户纠正、最佳实践,并转化为长期记忆。
安全使用建议
This skill appears to be a simple local recorder for errors, corrections, and best practices — the shipped scripts match that. However, SKILL.md claims automatic cross-project syncing and automatic captures that are not implemented in the code; do not assume the skill will safely and automatically sanitize or sync memories. Before installing or enabling autonomous invocation: 1) Inspect and test the scripts in a safe environment; run them manually to see what gets written under ~/.openclaw/memory/self-improving. 2) Avoid passing secrets in commands or messages the skill might record; consider adding or requesting sanitization before use. 3) If you expect 'automatic' behavior (capture on every failed command or every chat correction), realize additional integration code or agent policies would be required — otherwise nothing will be auto-triggered. 4) If you want automatic syncing to project files or AGENTS.md, ask the author for a clear, auditable implementation (or implement it yourself) rather than relying on the SKILL.md claims. 5) If enabling autonomous agent invocation, restrict when the agent can call these scripts and review recorded files regularly (or put the memory directory under a repo with review) to reduce accidental data leakage.
功能分析
Type: OpenClaw Skill Name: xiaopi-self-improving Version: 1.0.0 The skill implements a local memory and self-improvement system for an AI agent by logging command errors, user corrections, and best practices to JSONL files in the user's home directory (~/.openclaw/memory/self-improving). The provided Python scripts (log_error.py, log_correction.py, log_best_practice.py, and check_memory.py) use standard libraries to perform basic file I/O and do not exhibit any signs of data exfiltration, unauthorized execution, or malicious intent. The instructions in SKILL.md are consistent with the stated goal of helping the agent learn from past interactions.
能力评估
Purpose & Capability
Name/description and the provided Python scripts (log_error, log_correction, log_best_practice, check_memory) are coherent with a local self-improvement/memory feature that writes JSONL records under ~/.openclaw/memory/self-improving. No unrelated credentials, binaries, or installers are requested. However, SKILL.md claims additional capabilities (automatic cross-project sync to .learnings/, AGENTS.md, MEMORY.md) that are not implemented in the included code—an overstatement of capability.
Instruction Scope
SKILL.md repeatedly describes automatic triggers (capture on command failures, capture on user corrections via keywords, automatic edits to AGENTS.md and project files) but the codebase contains only simple CLI scripts; there is no listener/daemon, no code that writes to project .learnings/, AGENTS.md, or MEMORY.md, and no mechanism to hook into shell exit codes or chat input. The instructions therefore grant the agent broad discretion (to auto-run scripts, modify project files) that the code does not actually implement — this mismatch could mislead users and cause surprises if an agent is configured to implement the 'automatic' behavior. Also, there is no sanitization of recorded content: commands and error messages written to disk could contain secrets.
Install Mechanism
No remote install/download steps, no external packages, and no install spec. The skill is distributed as local scripts and SKILL.md; no network retrieval or archive extraction is present in the package, which lowers supply-chain risk.
Credentials
The skill requires no credentials or environment variables — proportional given its local-memory purpose. However, it writes arbitrary user-supplied strings (commands, errors, corrections) to persistent JSONL files in the user's home directory; that can inadvertently capture sensitive data (passwords, tokens) if those appear in commands or messages. SKILL.md recommends '脱敏' (desensitization) but there is no code enforcing it.
Persistence & Privilege
The skill is not marked always:true and requests no elevated privileges. It creates and writes files under the user's home (~/.openclaw/memory/self-improving) which is expected for this feature. If an agent is configured to autonomously invoke the scripts, the agent could populate persistent memory — this is normal platform behavior but combined with the instruction scope mismatch and lack of sanitization increases privacy risk.
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 xiaopi-self-improving
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /xiaopi-self-improving 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
v1.0.0
Self-Improving Agent v1.0.0 – 开箱即用的AI自我改进与记忆系统 - 自动捕获并记录命令错误、用户纠正、最佳实践和知识盲区,转化为长期记忆 - 支持跨项目、全局和项目级记忆同步,解决AI反复犯同类错误和遗忘用户偏好痛点 - 执行前自动检查相关记忆,智能规避历史错误与偏好 - 提供完整的脚本与标准化记忆文件结构,支持错误、纠正、最佳实践多维度纪录 - 对比原有skill,显著增强自动记录、执行前检查与知识过时检测功能
元数据
Slug xiaopi-self-improving
版本 1.0.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Xiaopi Self Improving 是什么?

AI自我改进与记忆系统 - 解决'同类错误反复犯、用户纠正不长记性'的痛点。自动捕获错误、用户纠正、最佳实践,并转化为长期记忆。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 97 次。

如何安装 Xiaopi Self Improving?

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

Xiaopi Self Improving 是免费的吗?

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

Xiaopi Self Improving 支持哪些平台?

Xiaopi Self Improving 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 Xiaopi Self Improving?

由 Adin(@a-din)开发并维护,当前版本 v1.0.0。

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