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概要と使いどころ
Provides patterns to configure AWS RDS (Aurora, MySQL, PostgreSQL) with Spring Boot applications. Configures HikariCP connection pools, implements read/write splitting, sets up IAM database authentication, enables SSL connections, and integrates with AWS Secrets Manager. Use when setting up RDS connections in Spring Boot, configuring connection pooling, or managing database credentials securely.
日本語の概要は準備中です。原文の説明を表示しています。
Use when implementing caching, session storage, rate limiting, or any Redis integration. Covers cache-aside pattern, key naming, TTL strategy, and serialization config.
日本語の概要は準備中です。原文の説明を表示しています。
Use when integrating LLMs, chat clients, embeddings, RAG pipelines, or AI agents into Spring Boot. Covers Spring AI ChatClient, prompt templates, embeddings, vector stores, and structured output. Use when user mentions Spring AI, LLM, ChatGPT, Claude, RAG, embeddings.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building MCP (Model Context Protocol) servers in Java/Spring Boot. Covers tool registration, resource exposure, prompt templates, and production deployment using the official MCP Java SDK. Use when user mentions MCP, AI agent integration, or tool calling.
日本語の概要は準備中です。原文の説明を表示しています。
Use when writing tests of any kind — unit, slice, or integration. Covers test structure, naming conventions, Mockito patterns, @WebMvcTest, @DataJpaTest, and Testcontainers setup.
日本語の概要は準備中です。原文の説明を表示しています。
Use when adding monitoring, metrics, logging, or tracing to Spring AI or LLM integration code. Covers token tracking, latency measurement, cost estimation, and prompt/response logging. Use when user mentions AI monitoring, token costs, or LLM observability.
日本語の概要は準備中です。原文の説明を表示しています。
Generate a structured test plan for a feature or module — covers unit, integration, contract, and edge cases without writing any implementation code.
日本語の概要は準備中です。原文の説明を表示しています。
Builds reusable Convex components with isolated tables and app-facing APIs. Use for new components, reusable backend modules, integrations, or component boundary work.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
日本語の概要は準備中です。原文の説明を表示しています。
Build production-ready Web3 applications, smart contracts, and decentralized systems. Implements DeFi protocols, NFT platforms, DAOs, and enterprise blockchain integrations.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "model agent mental states", "implement BDI architecture", "create belief-desire-intention models", "transform RDF to beliefs", "build cognitive agent", or mentions BDI ontology, mental state modeling, rational agency, or neuro-symbolic AI integration.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Weights & Biases SDK for .NET. ML experiment tracking and model management via Azure Marketplace. Use for creating W&B instances, managing SSO, marketplace integration, and ML observability.
日本語の概要は準備中です。原文の説明を表示しています。
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
日本語の概要は準備中です。原文の説明を表示しています。
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
日本語の概要は準備中です。原文の説明を表示しています。
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.
日本語の概要は準備中です。原文の説明を表示しています。
AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any "make slides", "create a deck", or "slides from this document" request.
日本語の概要は準備中です。原文の説明を表示しています。
Android data layer implementation guide. Provides comprehensive patterns for Room Database (Entity, DAO, Migration), DataStore (Preferences), Repository layer design, and common pitfalls. Use when implementing local data storage, cache strategies, or data source integration in Android projects.
日本語の概要は準備中です。原文の説明を表示しています。
Validate feature-level integration after all tasks are implemented. Checks cross-task consistency, full test suite, and overall spec coverage.
日本語の概要は準備中です。原文の説明を表示しています。
Independent quality assurance for one SDD Composy task in qa_required: CA coverage, unit/integration/E2E, accessibility, responsiveness, environment, and evidence inventory, producing the QA report and requesting evidence_required. Use when a task finished execution — 'rodar o QA da task', 'testar a TASK-003', 'validar a implementação'. Do NOT use for code review (sdd-review), the final verdict (sdd-verify), or test runs outside an SDD task.
日本語の概要は準備中です。原文の説明を表示しています。
Use when about to claim work is complete, fixed, or passing, and when a finished feature needs adversarial verification before integration
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants tests planned for existing code or a test audit — unit, integration, E2E scenarios exportable to Playwright, playwright-cli UI checks, a coverage matrix — 'criar testes para o UserService', 'plano de testes E2E do login', 'auditar a cobertura'. Writes .planning/feat/features/{slug}/plan.md. Do NOT use for code review (feat-review), for implementing features (feat-feature) or to run an existing plan (feat-exec).
日本語の概要は準備中です。原文の説明を表示しています。
Use Neon serverless Postgres with branching, connection pooling, and instant scalability for modern applications with Prisma or Drizzle ORM integration. Use when setting up serverless Postgres databases, implementing database branching for preview environments, configuring connection pooling, optimizing for serverless cold starts, using Prisma with Neon, implementing database migrations, scaling databases automatically, or building applications on Vercel/Netlify with Postgres.
日本語の概要は準備中です。原文の説明を表示しています。
Set up and maintain continuous integration and continuous deployment pipelines with GitHub Actions, GitLab CI, Jenkins, or similar tools to automate testing, building, and deployment. Use when configuring automated builds, setting up test automation, implementing deployment automation, creating release workflows, managing environment deployments, configuring build caching, implementing blue-green deployments, setting up rollback strategies, or automating the entire software delivery pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," "building many pages for SEO," "pSEO," "generate 100 pages," "data-driven pages," or "templated landing pages." Use this whenever someone wants to create many similar pages targeting different keywords or locations. For auditing existing SEO issues, see seo-audit. For content strategy planning, see content-strategy.
日本語の概要は準備中です。原文の説明を表示しています。