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概要と使いどころ
Create production-ready GitHub Actions workflows for automated testing, building, and deploying applications. Use when setting up CI/CD with GitHub Actions, automating development workflows, or creating reusable workflow templates.
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。
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API 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。
OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
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 complete, production-ready application from an OpenAPI specification
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 RAG pipelines and persistent agent memory using Pinecone as the vector database backend. ALWAYS USE THIS SKILL when the user mentions Pinecone, wants to index documents for semantic search, build a retrieval-augmented generation system, store agent memory across sessions, implement hybrid search, or connect an LLM to a searchable knowledge base — even if they don't say "Pinecone" explicitly. Also use when the user asks about vector databases for RAG, namespace isolation for multi-tenant agents, embedding pipelines, or scaling a knowledge base beyond what local storage can handle. DO NOT use for local-only vector stores (Chroma, FAISS, pgvector) or pure keyword search with no semantic component.
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 an outage, production incident, or significant service degradation has occurred and the team needs to write a structured blameless post-mortem. Triggers on phrases like "write a post-mortem", "incident review", "what went wrong", "outage report", "root cause analysis", or "RCA". Covers timeline reconstruction, contributing factor analysis, impact quantification, and action item generation with owners.
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。
Design or review infrastructure, deployment, CI/CD, Docker, Kubernetes, health checks, rollback, feature flags, production readiness, and mobile release workflows. Use for DevOps, platform, container, pipeline, or release tasks.
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 production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.
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 Python + BigQuery pipelines for cost safety, idempotency, and production readiness. Returns a structured report with exact patch locations.
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。
Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.
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。
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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。
Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"
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。
Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.
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。
Diagnose the current OMC session or repo state using logs, traces, state, and focused reproduction
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。
Deploys Llama Guard 3 safety classification, NeMo Guardrails programmable dialogue rails, and LLM Guard input/output scanner pipelines as complementary runtime defenses that inspect and constrain LLM prompts and responses. Use when adding a production runtime safety layer to an LLM, RAG, or agent application to block jailbreaks, prompt injection (OWASP LLM01), toxic content, or sensitive-data leakage before it reaches or leaves the model.
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 whenever a developer wants to turn an idea into a complete, production-ready, end-to-end system plan BEFORE writing any code. Trigger on 'plan this system', 'design the architecture for', 'help me blueprint', 'deep plan for X', 'break this idea into components', 'expand into action points', 'full implementation plan', or when the user pastes a project idea wanting architecture, components, pipelines, and file-level execution mapped out. Casual phrasing also triggers: 'help me think this through end-to-end', 'plan before coding'. Also covers living-workspace patterns: self-improving knowledge bases, reflection loops with auditor agents, four-agent teams, schema-as-code, wiki health scoring. **Resume triggers**: 'where did we leave off', 'continue this plan', 'resume my blueprint' - rehydrates state from disk via SESSION.md/NEXT.md/decisions/. Web research is mandatory every invocation.
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。
PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.
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。
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models. Use when: azure function, azure functions, durable functions, azure serverless, function app.
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。
Master of defensive Bash scripting for production automation, CI/CD pipelines, and system utilities. Expert in safe, portable, and testable shell scripts.
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。
Automated Android CI/CD pipeline to Google Play — supports TWA, React Native, Flutter, and native Android. Run npx android-cicd to set up keystore generation, GitHub Secrets, and a multi-stage workflow (internal/alpha/beta/production) with auto-bump versionCode.
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。
Instantly provision production-ready Postgres databases with Neon Instagres. Use when setting up databases, when users mention PostgreSQL/Postgres, database setup, or need a development database. Works with Drizzle, Prisma, raw SQL.
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。
Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.
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。
Translate Figma nodes into production-ready code with 1:1 visual fidelity using the Figma MCP workflow (design context, screenshots, assets, and project-convention translation). Trigger when the user provides Figma URLs or node IDs, or asks to implement designs or components that must match Figma specs. Requires a working Figma MCP server connection.
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 the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.
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。