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Found 1,152 Skills
Analyze application and system logs to identify errors, patterns, and root causes. Use log aggregation tools and structured logging for effective debugging.
4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.
Use when working with debugging toolkit smart debug
Systematic debugging that identifies root causes rather than treating symptoms. Uses sequential thinking for complex analysis, web search for research, and structured investigation to avoid circular reasoning and whack-a-mole fixes.
Build AdonisJS 6 + Inertia.js (React) applications from scratch through production. Full lifecycle - setup, pages, forms, shared data, debugging.
Start the Wasp dev server and set up full debugging visibility. This includes running the server (with access to logs), and connecting browser console access so Claude can see client-side errors. Essential for any development or debugging work.
This skill should be used when the user asks to "use the oracle" or "ask the oracle" for deep research, analysis, or architectural questions. The oracle excels at multi-source research combining codebase exploration and web searches, then synthesizing findings into actionable answers. Use for complex questions requiring investigation across multiple sources, architectural analysis, refactoring plans, debugging mysteries, and code reviews.
Scientific method expert for systematic bug investigation and root cause analysis. Use when users report bugs, crashes, unexpected behavior, or debugging requests. Applies hypothesis-driven investigation, controlled experiments, and rigorous validation across any programming language or platform.
Use ProviderObserver to log or debug Riverpod provider lifecycle; didUpdateProvider, ProviderScope observers, naming providers. Use when adding logging, analytics, or debugging for provider state changes. Use this skill when the user asks about ProviderObserver, logging Riverpod, or debugging provider updates.
Guides systematic PyTorch recommender-system model development across compact data facts, existing source code, configs, focused tests, and training loops without overloading context from broad research archives. Use when building, debugging, or refactoring torch/nn.Module RecSys models with Transformer/HSTU/attention blocks, sparse/dense/list feature fusion, pCVR/CTR heads, ablation axes, or competition codebases where many model ideas exist but bugs and interface drift must be controlled. 用来指导推荐系统 PyTorch 模型开发、Transformer/HSTU 建模、关键数据事实、特征交互、shape/debug、训练闭环和已有模型结构的系统化推进。
Guidance for implementing Knock in-app UI in a web app, with a focus on setting up, rendering, and debugging Knock guides in React.
Use when preparing, submitting, polling, or debugging Seedance 2.0 video generation jobs from product images, storyboard images, UGC scripts, voiceover copy, or promptPlan request JSON. Use for splitting scripts into render segments, uploading references, creating request JSON, submitting jobs through the hosted capability, polling predictions, and handing off local render paths.