# acc-error-memory

> Use this tool when you need to track and analyze error patterns in AI agents to improve their performance and decision-making. It solves problems related to identifying and mitigating biases, inaccuracies, and inconsistencies in AI outputs by providing detailed error logs and patterns. The tool accepts input data from AI agent interactions and outputs actionable insights and recommendations for error correction and model refinement.

Canonical page: https://skillsregistry.net/skills/impkind-acc-error-memory  
JSON: https://api.skillsregistry.net/v1/skills/impkind-acc-error-memory

## Description

Error pattern tracking for AI agents.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/impkind-acc-error-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": "impkind-acc-error-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/impkind-acc-error-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/impkind-acc-error-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