Clarvia Aeo Check

Clarvia AEO Check

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/clarvia-aeo-check from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses metadata.json plus ORIGIN.md as the provenance anchor for review.

Clarvia AEO Check

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Prerequisites, How It Works, AEO Score Interpretation, Common Pitfalls, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• 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
• Use when the request clearly matches the imported source intent: 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.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: 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.

Imported: Prerequisites

Add Clarvia MCP server to your config:

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

Examples

Example 1: Ask for the upstream workflow directly

Use @clarvia-aeo-check to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @clarvia-aeo-check against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @clarvia-aeo-check for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @clarvia-aeo-check using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: 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:

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

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• ✅ 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
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.

Imported Operating Notes

Imported: 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

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/clarvia-aeo-check, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Load only the files that materially change the answer, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @burp-suite-testing - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @burpsuite-project-parser - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @business-analyst - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @busybox-on-windows - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: 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

Imported: AEO Score Interpretation

Imported: 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

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.