ClaudeCursorWindsurfClineTool Quality & Evaluation

clarvia-aeo-check

Score any MCP server, API, or CLI for agent-readiness using Clarvia AEO (Agent Experience Optimization). Search 15,400+ indexed tools before adding them to your workflow.

31,392 stars
Complexity: easy

About this skill

The `clarvia-aeo-check` skill empowers AI agents to proactively assess the suitability of external services and tools before integrating them into workflows. Leveraging Clarvia's Agent Experience Optimization (AEO) framework, it scores any MCP (Multi-Cloud Platform) server, API, or CLI tool on critical dimensions: 1. **API Accessibility**: Evaluates ease of connection, documentation quality, and protocol adherence. 2. **Data Structuring**: Assesses consistency and clarity of data formats, crucial for an agent's parsing and processing. 3. **Agent Compatibility**: Determines how well the tool aligns with common AI agent interaction patterns and frameworks. 4. **Trust Signals**: Considers reliability, security, community support, and overall stability. By consulting a vast index of over 15,400 tools, this skill helps agents make informed decisions, prevent integration headaches, and ensure robust, optimized workflows.

Best use case

An AI agent needs to select the most reliable and 'agent-friendly' API for a new task; a developer wants to vet external tools for an agent's long-term operational stability; an agent is performing a pre-flight check on all its connected services to ensure optimal performance and security.

Score any MCP server, API, or CLI for agent-readiness using Clarvia AEO (Agent Experience Optimization). Search 15,400+ indexed tools before adding them to your workflow.

The agent will receive a comprehensive agent-readiness score for the specified tool, accompanied by a detailed breakdown across Clarvia's four AEO dimensions. This enables the agent to make data-driven decisions regarding tool selection, integration strategies, and potential areas for optimization, ultimately leading to more stable and efficient workflows.

Practical example

Example input

{
  "tool_name": "Google Cloud Vision API",
  "tool_type": "API"
}

Example output

{
  "tool_identifier": "Google Cloud Vision API",
  "agent_readiness_score": 9.1,
  "assessment": {
    "api_accessibility": {
      "score": 9.5,
      "details": "Well-documented REST API, high uptime, robust SDKs available."
    },
    "data_structuring": {
      "score": 8.9,
      "details": "Consistent JSON responses, clear object models, minor parsing needed for nested annotations."
    },
    "agent_compatibility": {
      "score": 8.8,
      "details": "Standard authentication (OAuth 2.0), widely compatible with common agent orchestration frameworks."
    },
    "trust_signals": {
      "score": 9.4,
      "details": "Mature product from a major vendor, strong security posture, extensive community and support."
    }
  },
  "recommendation": "Highly recommended for agent integration, offers excellent reliability and compatibility.",
  "clarvia_report_url": "https://clarvia.com/reports/google-cloud-vision-api-aeo-2026-03-27"
}

When to use this skill

  • Use this skill before integrating any new MCP server, API, or CLI into an AI agent's workflow; when evaluating multiple potential tools for a specific task to identify the best fit; to perform periodic health checks on existing tool integrations; or when seeking to optimize an agent's overall 'experience' with external services.

When not to use this skill

  • Do not use this skill for internal, proprietary tools where agent-readiness is guaranteed by design; when the tool is already extensively documented, integrated, and proven reliable within the agent's existing ecosystem; or if the Clarvia MCP server is not accessible or configured, making the check impossible.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/clarvia-aeo-check/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/clarvia-aeo-check/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/clarvia-aeo-check/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How clarvia-aeo-check Compares

Feature / Agentclarvia-aeo-checkStandard Approach
Platform SupportClaude, Cursor, Windsurf, ClineLimited / Varies
Context Awareness High Baseline
Installation ComplexityeasyN/A

Frequently Asked Questions

What does this skill do?

Score any MCP server, API, or CLI for agent-readiness using Clarvia AEO (Agent Experience Optimization). Search 15,400+ indexed tools before adding them to your workflow.

Which AI agents support this skill?

This skill is designed for Claude, Cursor, Windsurf, Cline.

How difficult is it to install?

The installation complexity is rated as easy. You can find the installation instructions above.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Clarvia AEO Check

## Overview

Before adding any MCP server, API, or CLI tool to your agent workflow, use Clarvia to score its agent-readiness. Clarvia evaluates 15,400+ AI tools across four AEO dimensions: API accessibility, data structuring, agent compatibility, and trust signals.

## Prerequisites

Add Clarvia MCP server to your config:

```json
{
  "mcpServers": {
    "clarvia": {
      "command": "npx",
      "args": ["-y", "clarvia-mcp-server"]
    }
  }
}
```

## When to Use This Skill

- Use when evaluating a new MCP server before adding it to your config
- Use when comparing two tools for the same job
- Use when building an agent that selects tools dynamically
- Use when you want to find the highest-quality tool in a category

## How It Works

### Step 1: Score a specific tool

Ask Claude to score any tool by URL or name:

```
Score https://github.com/example/my-mcp-server for agent-readiness
```

Clarvia returns a 0-100 AEO score with breakdown across four dimensions.

### Step 2: Search tools by category

```
Find the top-rated database MCP servers using Clarvia
```

Returns ranked results from 15,400+ indexed tools.

### Step 3: Compare tools head-to-head

```
Compare supabase-mcp vs firebase-mcp using Clarvia
```

Returns side-by-side score breakdown with a recommendation.

### Step 4: Check leaderboard

```
Show me the top 10 MCP servers for authentication using Clarvia
```

## Examples

### Example 1: Evaluate before installing

```
Before I add this MCP server to my config, score it:
https://github.com/example/new-tool

Use the clarvia aeo_score tool and tell me if it's agent-ready.
```

### Example 2: Find best tool in category

```
I need an MCP server for web scraping. Use Clarvia to find the 
top-rated options and compare the top 3.
```

### Example 3: CI/CD quality gate

Add to your CI pipeline using the GitHub Action:

```yaml
- uses: clarvia-project/clarvia-action@v1
  with:
    url: https://your-api.com
    fail-under: 70
```

## AEO Score Interpretation

| Score | Rating | Meaning |
|-------|--------|---------|
| 90-100 | Agent Native | Built specifically for agent use |
| 70-89 | Agent Friendly | Works well, minor gaps |
| 50-69 | Agent Compatible | Works but needs improvement |
| 30-49 | Agent Partial | Significant limitations |
| 0-29 | Not Agent Ready | Avoid for agentic workflows |

## Best Practices

- ✅ Score tools before adding them to long-running agent workflows
- ✅ Use Clarvia's leaderboard to discover alternatives you haven't considered
- ✅ Re-check scores periodically — tools improve over time
- ❌ Don't skip scoring for "well-known" tools — even popular tools can score poorly
- ❌ Don't use tools scoring below 50 in production agent pipelines without understanding the limitations

## Common Pitfalls

- **Problem:** Clarvia returns "not found" for a tool
  **Solution:** Try scanning by URL directly with `aeo_score` — Clarvia will score it on-demand

- **Problem:** Score seems low for a tool I trust
  **Solution:** Use `get_score_breakdown` to see which dimensions are weak and decide if they matter for your use case

## Related Skills

- `@mcp-builder` - Build a new MCP server that scores well on AEO
- `@agent-evaluation` - Broader agent quality evaluation framework

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