create-pr
GitHubにPull Requestを作成するスキル。コミット・プッシュ済みの状態で、現在のブランチの変更内容を分析し、適切なタイトルと説明文でPRを作成する。「PRを作成して」「プルリクエストを作って」「PR作って」などのトリガー...
Discover Testing & security skills, compare source repositories and read the instructions for each workflow.
GitHubにPull Requestを作成するスキル。コミット・プッシュ済みの状態で、現在のブランチの変更内容を分析し、適切なタイトルと説明文でPRを作成する。「PRを作成して」「プルリクエストを作って」「PR作って」などのトリガー...
実装計画をファイルに保存する。実装計画、タスク計画、作業計画を立てた後に使用。コンテキスト圧縮後も参照可能にするため doc/plans/ に保存する。トリガーキーワード: 実装計画, 計画保存, plan, 作業計画
Unified Specification-Driven Development (SDD) workflow. Auto-detects user intent and routes to correct phase. Handles the complete development lifecycle from product definition to implementation. Triggers on:...
Best-practice prompt engineering using research-backed patterns. Handles: transforming rough prompts into production-ready, debugging prompt issues, creating new prompts from scratch. ALWAYS researches via suba...
Comprehensive Next.js project setup from scratch following industry best practices. Use when creating new Next.js projects, requiring template selection, design system ideation, specifications, wireframes, impl...
Debug bugs and errors using intel-first approach with systematic root cause analysis. Use proactively when errors occur, tests fail, or unexpected behavior appears. MUST trace from symptom to root cause with Co...
Execute end-to-end tests for Nikita using Telegram MCP, Gmail MCP, Supabase MCP, Chrome DevTools MCP, and gcloud CLI. Use when verifying implementations, testing user journeys, validating integrations, performi...
Create detailed implementation plans from feature specs or bug reports with testable acceptance criteria. Use proactively when planning features, refactors, or fixes. Every task MUST have minimum 2 testable ACs...
Intelligence-first code analysis for bugs, architecture, performance, and security. Use proactively when investigating code issues, tracing dependencies, or understanding system behavior. MUST query project-int...
Audit and optimize website for AI search engines like ChatGPT, Perplexity, Google AI Overviews, and Claude. Use when discussing GEO (Generative Engine Optimization), SEO for AI, llms.txt, AI crawlers, structure...
Implement dynamic resolution scaling for React Three Fiber / Three.js by adjusting DPR based on measured FPS. Use when asked to add adaptive performance scaling, automatic DPR tuning, or a DynamicResScaler-styl...
React patterns for Effect Atom state, Suspense, hooks, component structure. Use for React UI work.
Tailwind conventions for composition, selectors, responsive, animation. Use for Tailwind code.
shadcn/ui registry usage, CLI workflows, component composition. Use when adding shadcn/ui components.
Effect patterns for Schema, errors, services, layers, Match, data. Use for Effect code and APIs.
Performance rules for React and Effect. Use for caching, rendering, data flow.
TypeScript naming, functions, control flow, types, modules. Use for code style and conventions.
UX patterns for states, forms, accessibility, copy, navigation. Use for UI behavior and a11y.
Helps with OSD JSON configuration files and schema. Use when editing config.json, modifying widget settings, changing fonts, or working with the JSON schema.
Helps with WASM compilation, building, and packaging. Use when discussing build targets, Makefile commands, build modes, or WASM compilation issues.
Helps with deploying OSD packages to sych.local. Use when discussing deployment, hot-reload, frontend updates, or gallery updates.
Helps with protobuf messages, updating proto submodules, and understanding the JonGUIState structure. Use when working with proto files, message fields, or state data.
Interactive Docker learning guide from basics to production, tailored for Python/FastAPI developers. This skill should be used when users want to learn Docker concepts, understand container fundamentals, practi...
Design and implement production-grade database layers using SQLModel with SQLAlchemy 2.0 patterns. This skill should be used when users need to create database models, configure engines/sessions, design schemas...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.