robustness-audit

What problem does it solve?

This Skill eliminates the risk of shipping code with latent runtime failures that pass all unit tests but break in production, including crashes, silent error swallowing, edge case mishandling, resource leaks, concurrency hazards, and security boundary holes that only appear under real-world usage conditions.

Core Features & Use Cases

• Defect-class guided audit: Uses a fixed 6-category taxonomy to prime distinct mental models for finding bugs, avoiding the "find all bugs" overwhelm that leads to noise or missed issues.
• Parallel subagent dispatch: Splits code into 3-5 natural surfaces and runs parallel reviews to cover more ground without context bloat.
• False positive verification: Actively checks high-severity findings against actual source code to filter out agent hallucinations, with a dedicated "verified wrong" section to build trust in results.
• Use cases: Pre-deployment hardening passes, FMEA-style code reviews, assessing unfamiliar or long-unmaintained codebases, investigating silent production failures where tests are all green, and finding bugs that can't be reproduced via live testing (no hardware, remote environment, etc.).

Quick Start

Request a robustness audit of your target codebase from your AI assistant, specifying any particular surfaces or defect classes you want prioritized if relevant.