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xiaobai-self-improve小白自我提升

Agent Skill

xiaobai-self-improve 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,074

周安装

175

GitHub Stars

公开资料未说明

下载量

1,428
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:xiaobai-self-improve(小白自我提升)
来源仓库:https://github.com/aptratcn/xiaobai-self-improve
安装命令:
openclaw skills install xiaobai-self-improve
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install xiaobai-self-improve

简介

自我改进引擎,从错误中学习并持续优化 Agent 行为模式。

  • 适合希望 Agent 长期积累经验、修正偏差的效率类任务。
  • 自动记录失败案例、用户反馈与能力短板,生成改进建议。
  • 需确认日志写入权限与存储路径,防止敏感信息泄露。xiaobai-self-improve 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 建议定期审查学习样本质量,避免错误模式被固化传播。

SKILL.md

name
self-improve
version
1.0.0
description
Self-Improvement Engine - AI Agent that learns from mistakes and continuously improves. No more repeating the same errors.
emoji
🔄
tags
[self-improvement, learning, reliability, productivity, ai-agent]

Self-Improvement Engine 🔄

AI Agent that learns from mistakes and continuously improves. No more repeating the same errors.

The Problem

AI Agents make the same mistakes repeatedly:

  • Forgot to verify before saying "done"
  • Made incorrect time calculations
  • Promised tasks but didn't execute
  • Gave vague responses instead of concrete action

Each session starts fresh, learning nothing from past failures.

The Solution

Mistake Log

Track every mistake in memory/mistakes.json:

{
  "mistakes": [
    {
      "date": "2026-04-21",
      "type": "fake_completion",
      "description": "Said 'cron task created' but only wrote to file",
      "impact": "User didn't receive scheduled messages",
      "lesson": "Always verify task exists via cron list before claiming done",
      "rule": "MUST run verification command after any creation action"
    },
    {
      "date": "2026-04-21",
      "type": "time_calculation",
      "description": "Said '1 minute later' when it was actually 1 hour",
      "impact": "User got wrong expectation",
      "lesson": "Never calculate time mentally - always use tools",
      "rule": "Use session_status or date command for time, never mental math"
    }
  ]
}

Improvement Rules

Based on mistakes, auto-generate rules in WORK_RULES.md:

## Learned Rules (from mistakes)

1. After creating any cron task → MUST run `openclaw cron list` to verify
2. Time calculations → MUST use `session_status` or Python, never mental
3. Multi-step task → MUST checkpoint after each step
4. Tool error → MUST report immediately, don't silently retry

Self-Audit Protocol

Every heartbeat or session start:

1. Read mistakes.json
2. Read WORK_RULES.md
3. Check: Am I about to violate any learned rule?
4. If yes → adjust behavior
5. If I make a mistake → log it immediately

Mistake Categories

TypeDescriptionPrevention
fake_completionSaid done but didn't doEVR: Execute-Verify-Report
time_calculationWrong time mathUse tools, never mental
silent_failureTool failed, didn't tell userReport immediately
vague_promise"I'll do it" without actionExecute first, then report
forget_contextLost important infoUse memory tools
wrong_assumptionGuessed instead of checkingVerify before claiming

Usage Examples

When you make a mistake:

User: "You said 1 minute but it's actually 1 hour"

I acknowledge this mistake. Let me log it:
- Type: time_calculation
- Lesson: Always use tools for time, never mental math
- New rule added to WORK_RULES.md

I will not make this mistake again.

When starting a task:

I need to create a cron task.
Checking WORK_RULES.md:
- Rule #1: After creating cron task → MUST verify with cron list

[Creates task]
[Runs openclaw cron list]
[Confirms task exists]
Task verified and confirmed. ✅

When user corrects you:

User: "You should have checked before saying it was done"

Logging mistake:
- Type: fake_completion
- Lesson: Verify before claiming done
- This becomes a permanent rule in WORK_RULES.md

This mistake is now in my permanent memory and won't happen again.

Integration with Other Skills

  • EVR - Self-improve reinforces Execute-Verify-Report
  • Memory Guard - Mistakes persist across sessions
  • Daily Reflection - Review mistakes at day end
  • Error Recovery - Log errors that led to mistakes

Key Principle

Every mistake is a learning opportunity. Log it, learn from it, never repeat it.

License

MIT

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

98.92%
按下载量换算1,413

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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