# agent-audit

> Use this tool when you need to evaluate the efficiency and effectiveness of your AI agent setup, identifying areas for improvement in performance, cost, and return on investment (ROI). It analyzes your agent's configuration and provides insights on optimizing its performance, helping you solve problems related to resource allocation and budgeting. By using agent-audit, you can expect input on agent setup and output on performance metrics and recommendations for improvement.

Canonical page: https://skillsregistry.net/skills/sharbelayy-agent-audit  
JSON: https://api.skillsregistry.net/v1/skills/sharbelayy-agent-audit

## Description

Audit your AI agent setup for performance, cost, and ROI.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-05-17

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/sharbelayy-agent-audit)

## 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": "sharbelayy-agent-audit"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sharbelayy-agent-audit` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sharbelayy-agent-audit/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