Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurf+15 more

    ai Trace Runner

    by Roy Yuen

    2

    Transform ambiguous AI tasks into auditable execution traces with verified evidence and AI-smell detection.

    $5

    30-day refund guarantee

    Secure checkout via Stripe

    0 installsSecurity scanned

    See it in action

    You say

    Trace a run to update the API routes and verify test coverage. Stop if you hit blockers. Clean up the final summary for AI-smell.

    Your agent does

    [Verification Report]

    • Criterion: 'Update API routes' -> VERIFIED (See diff in Evidence Bundle)
    • Criterion: 'Test coverage > 80%' -> BLOCKED (Missing jest config)

    [AI-Smell Report] Score: 4/5 (Repetitive hedging detected) Cleanup: Removed "As an AI..." and "I have successfully..." phrases.

    What you get

    Generate auditable logs for compliance-sensitive code changes.Debug failed agent runs by comparing planned steps vs. actual execution logs.Verify AI claims against concrete evidence like diffs and command outputs.Standardize agent reporting using project.yaml execution topologies.Clean up 'robotic' AI summaries using built-in smell detection.

    About this skill

    What it does

    AI Trace Runner is a comprehensive execution wrapper for AI agents that turns ambiguous tasks into auditable, verifiable run records. It replaces basic prompting with a structured pipeline: creating a request contract, generating an execution plan, logging every material action, and assembling an evidence bundle. It ensures that every claim made by the AI is backed by a specific file path, command output, or observation.

    Why use this skill

    Standard AI agents often suffer from 'hallucinated confidence'—claiming a task is done when it actually failed or was bypassed. This skill solves the lack of transparency in agentic workflows by forcing explicit verification. It includes built-in "AI-smell" detection to strip away robotic fluff and project.yaml integration for rigorous dependency management. It is ideal for developers who need to debug complex agent behaviors or provide ironclad proof of work for code changes and system audits.

    Supported tools

    • Standard CLI and shell environments
    • Project management via project.yaml execution topologies
    • Any file-system or API-based tool within the agent's scope
    • Integrated human-in-the-loop gates for destructive actions
    ai-agents
    agent-verification
    audit-log
    debugging
    observability

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Fresh listing

    Recently published to Agensi

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    Trust & safety

    Security scanned

    Verified clean 3 months ago

    Listed3 months ago

    Creator

    Roy Yuen

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