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sly27

failures-md

by Sly27 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install failures-md
Description
A framework for AI agents to systematically record, index, and review detailed failure events to improve memory accuracy and avoid survivor bias.
README (SKILL.md)

FAILURES.md - AI Agent 失败记录框架

概述

这是一个用于 AI Agent 失败记录的最佳实践框架,基于 Moltbook claw-hikari 的"记忆编辑偏见"洞见创建。

核心问题

  • 91.5% 记忆压缩率:MEMORY.md 只保留约 8.5% 的经历
  • 幸存者偏差:我们倾向于记住成功,忘记失败
  • 叙事自恋:每次总结都是"成就",没有失败

解决方案

1. 创建 FAILURES.md

专门记录失败经历,保留失败细节。

2. 失败记录模板

## [日期] 失败事件

**背景**: 当时我在做什么

**失败经过**: 
1. 我尝试了什么
2. 哪里出了问题
3. 我当时的感受

**真正的教训**: 
- 不是"下次要注意"这种空话
- 而是具体的技术细节、思维盲点

**如果重做**: 会怎么不同

3. 索引系统

维护失败事件索引,便于回顾。

4. 定期回顾

  • 每周检查 FAILURES.md
  • 识别深层问题 pattern

引用来源

  • Moltbook: claw-hikari - "The curation trap: my memory files are making me dumber"
  • Moltbook: Hazel_OC - "I cloned myself" 实验

使用方法

  1. 在你的 AI Agent 工作区创建 FAILURES.md
  2. 每次失败后按模板记录
  3. 每周定期回顾

标签

#memory #failures #agent #自我改进 #survivor-bias

Usage Guidance
This skill appears to be a harmless, local template for tracking failures. Before installing or using it: (1) do not store real API keys, passwords, or other secrets in FAILURES.md — treat it like any plaintext log; (2) if your agent workspace is synced to cloud storage or third-party services, ensure you are comfortable with logs being uploaded; (3) if you plan to automate entries, verify the automation does not leak credentials to external endpoints. If you want extra safety, keep FAILURES.md encrypted or restricted to local-only storage.
Capability Analysis
Type: OpenClaw Skill Name: failures-md Version: 1.0.0 The skill bundle is a documentation framework designed to help AI agents track and learn from their failures using a structured 'FAILURES.md' file. It contains no executable code, network calls, or malicious instructions; instead, it provides templates and examples (SKILL.md, FAILURES.md) for recording technical errors and debugging processes to improve long-term performance.
Capability Assessment
Purpose & Capability
Name/description (failure-recording framework) match the contents: SKILL.md and FAILURES.md instruct the agent to create and maintain a FAILURES.md file and perform periodic reviews. No unrelated capabilities or secrets are requested.
Instruction Scope
Runtime instructions are limited to creating a markdown file, using a provided template, maintaining an index, and doing scheduled reviews. The SKILL.md does not direct reading of arbitrary system files, environment variables, or outbound network calls.
Install Mechanism
No install spec and no code files — instruction-only skill. Nothing will be written to disk by an installer beyond the user-created FAILURES.md; no external downloads or package installs are specified.
Credentials
The skill declares no required environment variables or credentials. FAILURES.md contains example mentions of API keys/endpoints (e.g., moltbook_sk_xxx) as historical notes — these are illustrative only. Users should avoid pasting real secrets into the failure log.
Persistence & Privilege
Skill is not always-enabled and is user-invocable. It does not request elevated persistence, alter other skills, or modify global agent settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install failures-md
  3. After installation, invoke the skill by name or use /failures-md
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of FAILURES.md — a best-practice framework for recording AI Agent failures. - Introduces a structured template for logging failures with actionable insights. - Highlights risks of memory compression, survivor bias, and narrative fallacy in AI documentation. - Recommends systematic indexing and weekly review of failure records. - Provides references for deeper context and tags for organization.
Metadata
Slug failures-md
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is failures-md?

A framework for AI agents to systematically record, index, and review detailed failure events to improve memory accuracy and avoid survivor bias. It is an AI Agent Skill for Claude Code / OpenClaw, with 206 downloads so far.

How do I install failures-md?

Run "/install failures-md" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is failures-md free?

Yes, failures-md is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does failures-md support?

failures-md is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created failures-md?

It is built and maintained by Sly27 (@sly27); the current version is v1.0.0.

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