# auto-improve

> auto-improve — mcben90-auto-improve. Use this tool when you need to automatically improve performance by learning from errors and recognizing patterns. It solves problems related to iterative refinement and optimization, allowing for more efficient and effective processes. By providing input data and receiving output recommendations, users can leverage auto-improve to enhance their systems and workflows in various contexts.

Canonical page: https://skillsregistry.net/skills/mcben90-auto-improve  
JSON: https://api.skillsregistry.net/v1/skills/mcben90-auto-improve

## Description

Automatische Selbst-Verbesserung durch Fehler-Lernen und Pattern-Erkennung.

## 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:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/mcben90-auto-improve)

## 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": "mcben90-auto-improve"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mcben90-auto-improve` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mcben90-auto-improve/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