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Systematic debugging frameworks for finding and fixing bugs - includes root cause analysis, defense-in-depth validation, and verification protocols
Integrate Bunny.net services (CDN, Storage, Stream, DNS, Edge Scripting, Shield, Magic Containers, Optimizer, Database). Use when building with Bunny.net APIs, deploying to Bunny CDN, uploading files to Edge Storage, managing video streaming, configuring DNS zones, writing edge scripts, setting up WAF/DDoS protection, deploying containers, or optimizing images. Triggers on "bunny", "bunnycdn", "b-cdn", "pull zone", "edge storage", "bunny stream".
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
Build 3D web apps with Three.js (WebGL/WebGPU). Use for 3D scenes, animations, custom shaders, PBR materials, VR/XR experiences, games, data visualizations, product configurators.
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
Web testing with Playwright, Vitest, k6. E2E/unit/integration/load/security/visual/a11y testing. Use for test automation, flakiness, Core Web Vitals, mobile gestures, cross-browser.
Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm). Use for serverless, containers, CI/CD, GitOps, security audit.
| name | debugging |
| description | Systematic debugging frameworks for finding and fixing bugs - includes root cause analysis, defense-in-depth validation, and verification protocols |
| when_to_use | when encountering bugs, test failures, unexpected behavior, or needing to validate fixes before claiming completion |
| version | 1.0.0 |
| languages | all |
A collection of systematic debugging methodologies that ensure thorough investigation before attempting fixes.
Location: systematic-debugging/SKILL.md
Four-phase debugging framework: Root Cause Investigation → Pattern Analysis → Hypothesis Testing → Implementation. The iron law: NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST.
Location: root-cause-tracing/SKILL.md
Trace bugs backward through the call stack to find the original trigger. Don't fix symptoms - find where invalid data originated and fix at the source.
Location: defense-in-depth/SKILL.md
Validate at every layer data passes through to make bugs structurally impossible. Four layers: Entry Point → Business Logic → Environment Guards → Debug Instrumentation.
Location: verification-before-completion/SKILL.md
Run verification commands and confirm output before claiming success. The iron law: NO COMPLETION CLAIMS WITHOUT FRESH VERIFICATION EVIDENCE.
| Symptom | Sub-Skill |
|---|---|
| Test failure, unexpected behavior | systematic-debugging |
| Error appears in wrong location | root-cause-tracing |
| Same bug keeps recurring | defense-in-depth |
| Need to confirm fix works | verification-before-completion |
"Systematic debugging is FASTER than guess-and-check thrashing."
From real debugging sessions:
