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Klingai Audit Logging

Listed
jeremylongshore·vlatest·ai-ml·MIT

Automatically generates detailed audit logs of KlingAI actions, including prompts, responses, and system events for enhanced transparency.

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 jeremylongshore/tons-of-skills-marketplace --skill klingai-audit-logging -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

jeremylongshore

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.

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Automated safety checks

scanned

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Not scanned. none of the 396 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as jeremylongshore/claude-code-plugins-plus-skills.
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About this skill

What it does

The klingai-audit-logging skill provides detailed logging of AI agent actions and interactions. It captures specific events, including prompts sent to the model, responses received, and any intermediate steps taken during task execution. This allows for comprehensive auditing and debugging of agent behavior.

When to use it

  • Troubleshooting Agent Errors: When an agent produces unexpected or incorrect results, audit logs can help pinpoint the source of the problem (e.g., a flawed prompt or misinterpreted instruction).
  • Compliance & Security Audits: To demonstrate adherence to regulatory requirements and internal security policies by tracking all AI interactions.
  • Improving Agent Performance: Analyzing log data over time can reveal patterns and areas where agent prompts, workflows, or configurations could be optimized.
  • Debugging Complex Workflows: When agents are performing multi-step tasks, logging provides a clear record of each step's execution, aiding in debugging complex chains of operations.

Key capabilities

  • Detailed event logging (prompts, responses, intermediate steps)
  • Audit trail generation
  • Support for various AI agent workflows

Example prompts

  • "Enable audit logging for this conversation."
  • "Show me the last 10 audit log entries."
  • "Generate an audit report summarizing all actions taken by the agent in the past week."

Tips & gotchas

The effectiveness of this skill depends on clear and well-defined prompts to the AI agent. Ensure your prompts are specific enough to elicit the desired behavior, as ambiguous prompts can lead to unpredictable results that are difficult to trace through audit logs.