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Found 1,323 Skills
Apply production-ready best practices for weapp-vite projects. Use when creating or refactoring mini-program projects with weapp-vite, designing directory/config conventions, choosing subpackage and chunk strategy, enabling auto routes/components, setting CI/devtool workflows, or debugging build/output issues in `vite.config.ts` and `app.json`.
Systematic problem-solving techniques for stuck-ness. Techniques: simplification cascade (complexity spirals), collision-zone thinking (innovation blocks), meta-pattern recognition (recurring issues), inversion exercise (assumption constraints), scale game (uncertainty). Actions: simplify, analyze, recognize patterns, invert assumptions, scale thinking. Keywords: problem solving, complexity spiral, innovation block, stuck, simplification, meta-pattern, assumption inversion, scale uncertainty, breakthrough thinking, root cause, systematic analysis, Microsoft Amplifier, debugging approach, creative solution. Use when: complexity spiraling, hitting innovation blocks, seeing recurring patterns, constrained by assumptions, uncertain about scale, generally stuck on problems.
Consult external AIs (Gemini 2.5 Pro, OpenAI Codex, Claude) for second opinions. Use for debugging failures, architectural decisions, security validation, or need fresh perspective with synthesis.
Intelligent Core Web Vitals analysis with automated workflows and decision trees. Measures LCP, CLS, INP with guided debugging that automatically determines follow-up analysis based on results. Includes workflows for LCP deep dive (5 phases), CLS investigation (loading vs interaction), INP debugging (latency breakdown + attribution), and cross-skill integration with loading, interaction, and media skills. Use when the user asks about Core Web Vitals, LCP optimization, layout shifts, or interaction responsiveness. Compatible with Chrome DevTools MCP.
Debug applications using the dbg CLI debugger. Supports Node.js (V8/CDP), Bun (WebKit/JSC), and native code via LLDB (DAP). Use when: (1) investigating runtime bugs by stepping through code, (2) inspecting variable values at specific execution points, (3) setting breakpoints and conditional breakpoints, (4) evaluating expressions in a paused context, (5) hot-patching code without restarting (JS/TS), (6) debugging test failures by attaching to a running process, (7) debugging C/C++/Rust/Swift with LLDB, (8) any task where understanding runtime behavior requires a debugger. Triggers: "debug this", "set a breakpoint", "step through", "inspect variables", "why is this value wrong", "trace execution", "attach debugger", "runtime error", "segfault", "core dump".
Expert knowledge for Azure Synapse Analytics development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building, debugging, or optimizing Azure Synapse Analytics applications. Not for Azure Data Factory (use azure-data-factory), Azure Data Explorer (use azure-data-explorer), Azure Databricks (use azure-databricks), Azure Stream Analytics (use azure-stream-analytics).
Claudeception is a continuous learning system that extracts reusable knowledge from work sessions. Triggers: (1) /claudeception command to review session learnings, (2) "save this as a skill" or "extract a skill from this", (3) "what did we learn?", (4) After any task involving non-obvious debugging, workarounds, or trial-and-error discovery. Creates new Claude Code skills when valuable, reusable knowledge is identified.
Expert guidance for building production-grade AI agents and workflows using Pydantic AI (the `pydantic_ai` Python library). Use this skill whenever the user is: writing, debugging, or reviewing any Pydantic AI code; asking how to build AI agents in Python with Pydantic; asking about Agent, RunContext, tools, dependencies, structured outputs, streaming, multi-agent patterns, MCP integration, or testing with Pydantic AI; or migrating from LangChain/LlamaIndex to Pydantic AI. Trigger even for vague requests like "help me build an AI agent in Python" or "how do I add tools to my LLM app" — Pydantic AI is very likely what they need.
Use this skill when managing Linux servers, writing shell scripts, configuring systemd services, debugging networking, or hardening security. Triggers on bash scripting, systemd units, iptables, firewall, SSH configuration, file permissions, process management, cron jobs, disk management, and any task requiring Linux system administration.
Use KWC CLI (kd) to translate user requirements into deliverable KWC projects, components, page metadata, environment configurations, deployment and debugging results. This Skill is used when an Agent needs to initialize or extend a KWC project via scaffolding, split functions into KWC components, create or update *.page-meta.kwp, configure kd env, deploy metadata to the target environment, or guide the full process from requirements to KWC page rendering.
Go-specific code review with 6-phase methodology: Context, Automated Checks, Quality Analysis, Specific Analysis, Line-by-Line, Documentation. Use when reviewing Go code, PRs, or auditing Go codebases for quality and best practices. Use for "review Go", "Go PR", "check Go code", "Go quality", "review .go". Do NOT use for writing new Go code, debugging Go bugs, or refactoring -- use golang-general-engineer, systematic-debugging, or systematic-refactoring for those tasks.
Check GitHub Actions workflow status after git push using gh CLI. Reports CI status, identifies failing jobs, and suggests local reproduction commands. Use after "git push", when user asks about CI status, workflow failures, or build results. Use for "check CI", "workflow status", "actions failing", or "build broken". Do NOT use for local linting (use code-linting), debugging test failures locally (use systematic-debugging), or setting up new workflows.