Evidence-Driven Debug Mode for AI Agent Skills

Evidence-Driven Debug Mode for AI Agent Skills

The Evidence-Driven Debug Mode skill is a sophisticated tool designed to assist developers in identifying and rectifying complex bugs through runtime evidence collection. Unlike speculative fixes, this skill utilizes evidence-first debugging strategies to address bugs that cannot be easily reproduced or that persist despite previous attempts at fixing them.

What this skill does

• Restates the bug by outlining the observed versus the expected behavior succinctly.
• Follows the actual execution path from entry to failure, avoiding assumptions based on file names.
• Generates a list of 3–5 competing hypotheses and defines the runtime values or events needed to confirm or rule out each hypothesis.
• Implements temporary probes to garner runtime information necessary for identifying the root cause.
• Applies the smallest possible fix based on gathered evidence, verifies the resolution, and removes the temporary probes to maintain clean code.

Who it is for

This skill is aimed at developers and development teams who leverage AI coding agents such as Claude Code, Cursor, and Codex. It is particularly useful for those dealing with bugs that exhibit complex, runtime-dependent behaviors.

Use cases

• When a bug has multiple plausible causes that cannot be easily distinguished without runtime data.
• If previous attempts at bug fixing have failed to resolve the issue.
• When a failure occurs due to specific runtime state, timing, inputs, or environment, and understanding these dependencies is crucial.
• In scenarios where the user can reproduce the bug consistently but the underlying cause remains unclear.

Technical details

This skill operates effectively within environments that support file browsing, shell access, and code editing, making it compatible with a wide range of AI agents. Originally derived from the `pi-debug-mode` extension for the Pi coding agent, it offers portability across supported platforms, with Pi users having the option to install it via `pi install npm:pi-debug-mode`.

Source & Licence

This package is built on open-source work published by liush2yuxjtu (liush2yuxjtu/pi-debug-mode) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.