Agent Eval Coverage Audit

    2

    Audit your AI agent's evaluation coverage to identify missing release gates and production risks.

    $5

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    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    agent-eval-coverage-audit

    Example session with this skill installed

    Audit my Support Agent Pilot using .\sample-eval-config.json. The success goal is to resolve issues without escalation. Output the report and JSON to the current directory.

    • Read your context and instructions
    • Compiled the agent-eval-coverage-audit

    Audit Summary: 65% Coverage.
    CRITICAL GAP: Missing evaluation for 'Human Escalation' paths.

    REMEDIATION

    1. Add adversarial test cases for prompt injection.
    2. Implement semantic similarity gates in CI.
    3. Update eval-config.json to include latency percentiles.
    3. Update eval-config.json

    Connects securely to your tools. The creator never sees your data.

    What you get

    Identify blind spots in agent evaluation suites before production release.Generate client-ready audit reports in Markdown and JSON formats.Verify if CI/CD hooks adequately enforce safety and quality policies.Analyze execution traces to improve success definitions and test datasets.

    About this skill

    What it does

    This skill provides a professional-grade evaluation of your AI agent's testing infrastructure. It inspects evaluation configurations, sample datasets, CI/CD hooks, and policy checks to identify critical gaps in your release gates. It transforms technical debt into a structured remediation plan, ensuring your agent pilots are truly production-ready.

    Why use this skill

    Manual evaluation of your eval suite is meta-work that often gets skipped. This skill automates the process by analyzing your current test surface against industry best practices. Unlike simple prompts, it cross-references your system's success definitions with existing traces and configs to spot "false greens" and missing edge cases that could lead to production failures.

    Supported tools

    • Frameworks: Supports any JSON-based eval config (Promptfoo, LangSmith, etc.)
    • Environments: PowerShell, Python 3.x
    • Outputs: Generates executive-ready Markdown reports and machine-readable JSON for CI/CD integration

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

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    Recently published to Agensi

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    Security scanned

    Verified clean 5 months ago

    • Passed all security checks, Safe to install

    Listed5 months ago

    What's inside

    Frequently Asked Questions