# failure-memory

> Use this tool when you need to identify and learn from past mistakes to improve future decision-making. Failure-memory analyzes patterns of failure to prevent recurrence, solving problems of repeated errors and inefficiencies. It takes in data on past failures and outputs actionable insights to inform better choices.

Canonical page: https://skillsregistry.net/skills/leegitw-failure-memory  
JSON: https://api.skillsregistry.net/v1/skills/leegitw-failure-memory

## Description

Stop making the same mistakes — turn failures into patterns that prevent recurrence.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-05-21

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-05-21

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/leegitw-failure-memory)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "leegitw-failure-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/leegitw-failure-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/leegitw-failure-memory/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt