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Found 192 Skills
Storybook MCP server integration for component-aware AI development. Covers 6 tools across 3 toolsets (dev, docs, testing): component discovery via list-all-documentation/get-documentation, story previews via preview-stories, and automated testing via run-story-tests. Use when generating components that should reuse existing Storybook components, running component tests via MCP, or previewing stories in chat.
Diff-aware AI browser testing — analyzes git changes, generates targeted test plans, and executes them via agent-browser. Reads git diff to determine what changed, maps changes to affected pages via route map, generates a test plan scoped to the diff, and runs it with pass/fail reporting. Use when testing UI changes, verifying PRs before merge, running regression checks on changed components, or validating that recent code changes don't break the user-facing experience.
SOLID principles, hexagonal architecture, ports and adapters, and DDD tactical patterns for maintainable backends. Use when implementing clean architecture, decoupling services, separating domain logic, or creating testable architecture.
Redis semantic caching for LLM applications. Use when implementing vector similarity caching, optimizing LLM costs through cached responses, or building multi-level cache hierarchies.
Database and HTTP connection pooling patterns for Python async applications. Use when configuring asyncpg pools, aiohttp sessions, or optimizing connection lifecycle in high-concurrency services.
Advanced pytest patterns including custom markers, plugins, hooks, parallel execution, and pytest-xdist. Use when implementing custom test infrastructure, optimizing test execution, or building reusable test utilities.
Browser automation and content capture patterns for Playwright, Puppeteer, web scraping, and structured data extraction. Use when automating browser workflows, capturing web content, or extracting structured data from web pages.
Stores decisions and patterns in knowledge graph. Use when saving patterns, remembering outcomes, or recording decisions.
Prioritization frameworks — RICE, WSJF, ICE, MoSCoW, and opportunity cost scoring for backlog ranking. Use when prioritizing features, comparing initiatives, justifying roadmap decisions, or evaluating trade-offs between competing work items.
Porter's Five Forces, SWOT analysis, and competitive landscape mapping. Use when analyzing market position, evaluating competitive threats, building battlecards, or assessing industry dynamics.
Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off. This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation. Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility
Provides reverse engineering techniques for CTF challenges. Use when analyzing binaries, game clients, obfuscated code, esoteric languages, custom VMs, anti-debugging, anti-analysis bypass, WASM, .NET, APK (including Flutter/Dart AOT with Blutter), HarmonyOS HAP/ABC, Python bytecode, Go/Rust/Swift/Kotlin binaries, VMProtect/Themida, Ghidra, GDB, radare2, Frida, angr, Qiling, Triton, binary diffing, macOS/iOS Mach-O, embedded firmware, kernel modules, game engines, or extracting flags from compiled executables.