# errs

> errs — hegner123-errs. Use this tool when you need to simplify and standardize error messages from compilers and linters, converting verbose output into structured JSON for easier parsing and analysis. It solves the problem of cumbersome error handling by providing a compact and normalized output, making it ideal for use in development and testing workflows, especially with git. The tool takes compiler or linter output as input and produces structured JSON as output.

Canonical page: https://skillsregistry.net/skills/hegner123-errs  
JSON: https://api.skillsregistry.net/v1/skills/hegner123-errs

## Description

Compact error/lint parser MCP tool. Normalizes verbose compiler/linter output into structured JSON.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/hegner123/errs)

## 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": "hegner123-errs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/hegner123-errs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/hegner123-errs/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