Agent Reliability Audit

    2

    Turn raw agent traces and tool logs into professional production-readiness audits and remediation reports.

    $5

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    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+22 more

    agent-reliability-audit

    Example session with this skill installed

    Audit the Support Agent Pilot using sample-runs.json and tool-inventory.json. Define success as resolving issues without escalation and output the findings to report.md.

    • Read your context and instructions
    • Compiled the agent-reliability-audit

    RELIABILITY AUDIT SUMMARY: Support Agent Pilot

    FAILURE MODES

    • Infinite Loop (Tool A): 12% of runs (IDs: #42, #89)
    • Latency Spike: SearchTool avg 4.2s (Max 12.1s)

    REMEDIATION

    1. Implement retry jitter on SearchTool.
    2. Update system prompt to prevent recursive calls between Tools A & B.

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

    What you get

    Identify hidden agent loops and drift patterns in pilot run exportsMeasure tool call stability and identify high-latency hotspotsGenerate evidence-backed remediation plans for unstable AI agentsProduce professional Markdown audit reports for client or executive review

    About this skill

    Turn Agent Traces into Actionable Reliability Audits

    Moving an AI agent from a pilot to production requires more than just testing—it requires a systematic analysis of how the agent behaves under pressure. This skill analyzes exported run logs, traces, tool calls, and retries to identify the hidden failure modes that cause production outages.

    What it does

    • Pattern Detection: Identifies agent looping, drift, and latency hotspots in real-world transcripts.
    • Tool Stability Analysis: Correlates tool inventory against execution traces to find "flaky" integrations.
    • Evidence-Backed Reporting: Generates client-ready audit reports in Markdown and JSON with deep dives into recovery failures.
    • Remediation Guidance: Connects observed failures to specific architectural improvements.

    Why use this skill

    Prompting an AI to "find bugs" in logs often misses architectural context and statistical trends. This skill uses a structured approach to evaluate agent reliability across multiple runs simultaneously. It doesn't just look for errors; it looks for instability patterns that standard unit tests miss, providing a professional audit that stakeholders can trust before a full-scale rollout.

    Integration

    Compatible with Python-based workflows, it integrates seamlessly into CI/CD pipelines or developer workstations to analyze logs from frameworks like LangChain, CrewAI, or custom OpenAI implementations.

    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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    Trust & safety

    Security scanned

    Verified clean 6 months ago

    • Passed all security checks, Safe to install

    Listed6 months ago

    What's inside

    Frequently Asked Questions