What problem does it solve?
Debugging issues that involve browsers, editors, CDN/WAF layers, IM platforms, OS clipboards, or third-party SaaS often fails because the behavior lives outside your code. This Skill stops the cycle of repeated code-reasoning fixes that produce no-ops by forcing real environment data capture first.
Core Features & Use Cases
- Black-box identification checklist: Classifies whether a system is a black box based on control, documentation, debuggability, and predictability criteria.
- Data collection templates: Provides per-system capture recipes, such as reading clipboard MIME types via navigator.clipboard.read(), diffing outerHTML before and after paste, and using curl -v to inspect CDN/WAF headers.
- Case library with naming conventions: Ships real cases (CSDN paste list bug, CDN/WAF empty-body interception, proxy keyword misjudgment) plus templates for documenting new findings.
- Use Case: When a copied article renders as four "1." list items in CSDN but works in WeChat, use this Skill to capture the actual pasted HTML, discover the HTML-to-Markdown conversion drops the start attribute, and fix by merging adjacent lists before writing to the clipboard.
Quick Start
Ask the AI to debug a paste or third-party API issue using the external system debugging methodology and have it request real captured data before proposing any fix.