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failure-memory-log故障记忆记录

Agent Skill

failure-memory-log 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

12,735

周安装

536

GitHub Stars

2

下载量

4,460
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:failure-memory-log(故障记忆记录)
来源仓库:https://github.com/voidlight00/failure-memory-log
安装命令:
openclaw skills install failure-memory-log
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 failure-memory-log

简介

自动记录任务失败模式并提供解决方案建议的知识库系统。

  • 适合希望 Agent 持续积累经验、减少重复错误的长期协作场景。
  • 可捕获错误上下文、根因分析和修复方案形成知识条目。
  • 需开启日志写入权限并定期归档以避免存储溢出。failure-memory-log 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 建议结合人工审核机制,确保记录内容的准确性和实用性。

SKILL.md

name
failure-memory
description
Automatic failure pattern recording and recall system. Prevents repeating the same mistakes by logging errors with context, root cause, and resolution. Use when: (1) a command/task fails and you want to record why, (2) starting a new task and want to check for known pitfalls, (3) reviewing accumulated failure patterns for learning, (4) agent makes an error and needs to log it for future prevention. Triggers: 'log failure', 'check failures', 'failure report', 'what went wrong', 'mistake log', or any error/failure during agent work.

Failure Memory

Record failures. Learn from them. Never repeat them.

Core Concept

Every failure has three parts:

  1. What happened (error message, symptom)
  2. Why it happened (root cause)
  3. How to fix/avoid it (resolution)

This skill stores them in a searchable markdown file and provides a recall mechanism before starting similar tasks.

File Structure

memory/
└── failures.md      # All failure records (append-only log)

Recording a Failure

When an error occurs during work, append to memory/failures.md:

## [YYYY-MM-DD HH:mm] <short title>

- **Category:** <build|deploy|config|api|permissions|data|logic|network|dependency>
- **Context:** <what you were trying to do>
- **Error:** `<exact error message or symptom>`
- **Root Cause:** <why it happened>
- **Resolution:** <what fixed it>
- **Prevention:** <how to avoid next time>
- **Tags:** <comma-separated keywords for search>

When to Record

Record AUTOMATICALLY when:

  • A shell command exits non-zero and you identify why
  • An API call fails and you find the cause
  • A config/setup step fails and you resolve it
  • You catch yourself repeating a previously-solved mistake
  • A sub-agent reports an error with resolution

Do NOT record:

  • Transient network timeouts (unless pattern emerges)
  • Intentional test failures
  • User-cancelled operations

Pre-Task Recall

Before starting any significant task, search failures for relevant history:

grep -i "<keyword>" memory/failures.md

Or use memory_search if vector search is available:

memory_search query="<task description> failure error"

If matches found, mention them briefly:

⚠️ Known pitfall: [title] — [prevention tip]

Failure Report

When asked for a failure report or review, generate a summary:

  1. Read memory/failures.md
  2. Group by category
  3. Identify repeat patterns (same root cause appearing multiple times)
  4. Suggest systemic fixes for patterns

Report Format

# Failure Report — YYYY-MM-DD

## Stats
- Total: N failures recorded
- Top category: <category> (N occurrences)
- Repeat offenders: N patterns seen 2+ times

## Repeat Patterns
### <pattern name>
- Seen: N times
- Root cause: <shared cause>
- Systemic fix: <recommendation>

## Recent Failures (last 7 days)
- [date] <title> — <resolution>

Initialization

Run scripts/init.sh to set up the failures file:

bash scripts/init.sh [memory_dir]

Default memory_dir: ./memory

Best Practices

  1. Be specific — "EACCES on /var/run/docker.sock" beats "permission error"
  2. Include the exact error — Future grep depends on it
  3. Tag generously — More tags = better recall
  4. Review monthly — Patterns reveal systemic issues
  5. Link to fixes — Reference commits, PRs, or config changes when possible

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

76.85%
按下载量换算3,428

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install failure-memory-log 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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