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auto-improving-agent汽车改良剂

Agent Skill

auto-improving-agent 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

4,819

周安装

207

GitHub Stars

公开资料未说明

下载量

1,689
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:auto-improving-agent(汽车改良剂)
来源仓库:https://github.com/omaression/auto-improving-agent
安装命令:
openclaw skills install auto-improving-agent
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 auto-improving-agent

简介

auto-improving-agent 用于记录任务执行中的错误、用户纠正和经验缺口,帮助 Agent 持续改进表现。

  • 适用于希望让 Agent 沉淀问题、修正行为并优化最佳实践的场景。
  • 通过 clawhub 安装,命令为 openclaw skills install auto-improving-agent,需结合来源仓库进一步确认具体用法。
  • 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操作。
  • 当前功能描述基于原始 README,实际能力以官方文档为准。

SKILL.md

name
self-improving-agent
description
Automatically capture corrections, failures, and reusable discoveries into .learnings/ files using signal-based filtering. Triggers when the user corrects the agent, a tool/command fails in a reusable way, or a better approach is discovered. Also handles periodic retention scoring and promotion of proven patterns into SOUL.md, AGENTS.md, or TOOLS.md.

Self-Improving Agent

Capture what matters. Ignore noise. Promote proven patterns. Automate all of it.

Source of truth

  • .learnings/LEARNINGS.md — corrections, env configs, reusable fixes, architecture decisions
  • .learnings/ERRORS.md — tool/command failures with fixes
  • .learnings/FEATURE_REQUESTS.md — missing capabilities worth tracking
  • .learnings/ARCHIVE.md — entries scored out during retention sweeps (never injected into context, but searchable)

Write gate

Before logging anything, the candidate must pass at least ONE filter:

FilterWeightDescription
CorrectionALWAYSOmar explicitly corrected the agent
RecurrenceHIGHSame issue hit 2+ times (check existing entries)
Cost-to-rediscoverHIGHWould take >2 tool calls to figure out again
Blast radiusMEDIUMAffects multiple skills, projects, or workflows
Decay riskMEDIUMNon-obvious env/config detail that changes rarely

If NONE match → do not log. This replaces any arbitrary line-count threshold.

Never log:

  • routine successes
  • facts obvious from docs or code
  • one-off tasks with no recurrence potential
  • anything already in MEMORY.md, SOUL.md, USER.md, or AGENTS.md

Entry format

LEARNINGS.md:

- [YYYY-MM-DD] [Category]: [Actionable takeaway]

Categories: Correction, Env, Workflow, Testing, Skills, Git, Architecture

ERRORS.md:

- [YYYY-MM-DD] [Tool]: [What failed] → [Fix]

Mark fixed items with [fixed]. Delete stale entries during retention sweeps.

Retention gate

Instead of a hard line cap, score each entry periodically:

SignalScore
Referenced or applied in last 30 days+3
Matches active project context+2
Direct correction from Omar+2
Has prevented a repeat error+3
Env/config still valid+1
Superseded by newer entry−5
>90 days old, never referenced−3

Action:

  • score ≥ 2 → keep
  • 0 ≤ score < 2 → archive to .learnings/ARCHIVE.md
  • score < 0 → delete

Run this sweep during heartbeat maintenance (every ~3 days) or when LEARNINGS.md feels noisy.

Automated triggers

These fire without user prompting:

  1. Post-task scan: After multi-step tasks, check for retried commands, error→workaround sequences, or avoidable file reads. If found, evaluate against write gate and log if it passes.
  1. Session-start sweep: On .learnings/LEARNINGS.md read, flag entries >90 days old for retention scoring.
  1. Promotion detector: After logging, scan for entries with the same [Category] tag appearing 3+ times. If found, auto-suggest a one-liner promotion to:

- behavior/style → SOUL.md - workflow/process → AGENTS.md - tool/env gotcha → TOOLS.md

  1. Cross-session pattern detection: When memory_search returns a daily note describing a workaround, check if .learnings/ already has it. If not and it passes the write gate, log it.

Dedup

Before logging, scan existing entries for near-duplicates. If the lesson already exists, only update it if the new version is sharper or more general.

Quality bar

Every entry must help a future session avoid wasted work in under one glance.

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

81.06%
按下载量换算1,369

安全审计

VirusTotal

通过

ClawScan

通过

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。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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