# aiglare

> aiglare — nugehs-aiglare. Use this tool when you need to identify and flag unguarded Large Language Model (LLM) outputs that reach users or trigger side-effects. It analyzes code to detect vulnerable spots, providing a Command-Line Interface (CLI) and Model Control Plane (MCP) for seamless integration with git repositories. This tool solves security and reliability issues by ensuring LLM outputs are properly guarded and monitored.

Canonical page: https://skillsregistry.net/skills/nugehs-aiglare  
JSON: https://api.skillsregistry.net/v1/skills/nugehs-aiglare

## Description

Finds every spot where LLM output reaches a user or triggers a side-effect — and flags the unguarded ones. CLI + MCP.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **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/nugehs/aiglare)

## 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": "nugehs-aiglare"
    }
  }
}
```

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