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Trace Audit

Checked
joyco-studio·vlatest·security

Joyco-Studio's trace-audit analyzes system actions to identify anomalies, errors, and potential security breaches for enhanced accountability.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add joyco-studio/skills --skill trace-audit -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

joyco-studio

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned joyco-studio/skills at b19cfe3832.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
b19cfe3832
Manifest
skills/trace-audit/SKILL.md
Scanned
3 files, 412 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The trace-audit skill provides a mechanism to track and review actions taken by an AI agent. It allows users to examine the sequence of decisions made, including prompts used and responses generated. This capability is valuable for debugging agent behavior, understanding its reasoning process, and ensuring accountability.

When to use it

  • Debugging unexpected agent behavior: If an agent produces an undesirable outcome, trace-audit can help identify the steps that led to it.
  • Understanding complex decision processes: For agents handling intricate tasks, tracing their actions provides insight into how they arrive at conclusions.
  • Ensuring compliance and accountability: Audit trails are crucial for verifying adherence to guidelines or regulations in automated workflows.
  • Improving agent performance: By analyzing the trace data, you can identify areas where the agent's prompts or logic could be refined.

Key capabilities

  • Action tracking: Records prompts and responses.
  • Reviewable audit trails: Provides a history of agent actions for analysis.
  • Debugging assistance: Helps pinpoint sources of errors in agent behavior.

Example prompts

  • "Show me the trace for my last conversation with the agent."
  • "Can you generate an audit trail of the steps taken to complete task X?"
  • "Display the prompt and response history for this specific interaction ID."

Tips & gotchas

The effectiveness of trace-audit depends on the underlying implementation within the AI agent. Ensure that the agent is configured to enable tracing before initiating tasks you wish to audit.