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概要と使いどころ
Implementing the `Idempotency-Key` HTTP header pattern (Stripe-pioneered, IETF-standardizing) so retries don't double-charge or duplicate side effects — full Postgres schema with recovery-point state machine, fingerprint check, in-progress lock with 409 response, and 24h retention. Grounded in Stripe blog/docs, the IETF httpapi WG draft, and Brandur Leach's canonical implementation.
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Diagnose and eliminate the GraphQL N+1 resolver explosion using Facebook DataLoader's per-request batching, plus the second-order defenses (persisted queries, depth limits, cost analysis). Use when a GraphQL query that returns N items in a list triggers N+1 database round trips, when designing nested resolvers that load associations, when a list query times out under load, or when you need to budget query cost before resolvers run. NOT for REST-style endpoint design (use api-versioning-strategy), generic database query optimization (use database-query-optimizer), or schema design (use graphql-server-architect).
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PgBouncer, connection optimization, and pooling strategies for database performance. Activate on: connection pool, PgBouncer, database connections, pool size, connection limit, Prisma pool, Drizzle pool. NOT for: query optimization (use data-warehouse-optimizer), database schema design (use dimensional-modeler).
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 data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).
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。
Architect data fetching with TanStack Query v5, SWR, optimistic updates, prefetching, and cache invalidation strategies. Activate on: React Query, SWR, optimistic updates, cache invalidation, prefetching, stale-while-revalidate, infinite queries. NOT for: REST API design (use api-architect), database queries (use database skills), GraphQL schema (use graphql-expert).
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 DevOps engineer for CI/CD, IaC, Kubernetes, and deployment automation. Activate on: CI/CD, GitHub Actions, Terraform, Docker, Kubernetes, Helm, ArgoCD, GitOps, deployment pipeline, infrastructure as code, container orchestration. NOT for: application code (use language skills), database schema (use data-pipeline-engineer), API design (use api-architect).
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。
Validates agent outputs against schemas and quality criteria, scores confidence, detects hallucinations, monitors convergence, decides when to iterate, and synthesizes actionable feedback. Use when checking if a node's output is acceptable, scoring confidence, detecting fabricated content, deciding whether to re-execute, or generating improvement feedback. Activate on "validate output", "check quality", "confidence score", "hallucination check", "should we iterate", "improvement feedback". NOT for executing DAGs (use dag-runtime), planning DAGs (use dag-planner), or matching skills (use dag-skills-matcher).
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 build beautiful, accessible graphical interfaces — web, desktop (Electron/Tauri), and native (iOS/macOS/Android). Use for visual hierarchy and layout, color and theming (light/dark, semantic tokens, WCAG contrast), typography systems, motion and micro-interactions, accessibility, component systems and design tokens, responsive/adaptive layout, and platform-native idioms. The GUI counterpart to beautiful-cli-design. NOT for terminal/CLI output (use beautiful-cli-design) or API/data schemas.
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。
Application architecture patterns and code organization — clean architecture, hexagonal architecture, feature-based structure, dependency inversion, module boundaries, SOLID principles at module scale. Activate on "clean architecture", "hexagonal architecture", "feature-based structure", "dependency inversion", "module boundaries", "architecture pattern", "folder structure", "fat controller", "circular dependency", "IoC container". NOT for microservice decomposition (use microservices-patterns) or database schema design (use database-design-patterns).
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 safely evolve data models, schemas, migrations, queries, indexes, and ORM data-access boundaries. Discover the existing engine and migration source before proposing syntax.
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 review durable REST, GraphQL, RPC, or event API contracts: shape, compatibility, pagination, error semantics. Discovers existing consumers first. Not implementation, schema, or release.
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 backend changes end to end: endpoints, handlers, services, integrations, webhooks, jobs, authenticated access. Routes contracts to api-design-principles, schema to database.
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 review durable REST, GraphQL, RPC, or event-facing API contracts. Use for public or shared API contracts, endpoint/schema consistency, compatibility, pagination, error semantics, and API documentation. Discovers existing consumers and conventions before recommending a style.
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 backend service changes: API contracts, service boundaries, auth integration, reliability and delivery checks. Use for backend/API handlers, services, webhooks, jobs, or backend architecture changes. Routes schema/migrations to mk:database; security review to the existing security workflow.
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 performance optimization guidelines from Supabase. Apply when writing SQL, designing schemas, configuring RLS, or optimizing database performance.
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。
Assigns isolate identity at the right resolution for the question -- ANI/Mash species triage, 7-locus MLST historical comparability, cgMLST/wgMLST outbreak resolution (chewBBACA, BIGSdb, Ridom SeqSphere, EnteroBase HierCC), in-silico serotyping (SISTR/SeqSero2 Salmonella, SerotypeFinder E. coli, Kaptive Klebsiella, SeroBA pneumococcus, spa+SCCmec S. aureus), and lineage callers (TB-Profiler/Mykrobe barcode for MTBC, Pangolin + Nextclade for SARS-CoV-2, PopPUNK GPSC for S. pneumoniae). Use when typing bacterial isolates for surveillance or outbreak investigation, choosing between cgMLST allele distance and core-SNP distance for cluster definition, harmonising calls across schemas/database versions, assigning MTBC lineage with the Napier 90-SNP barcode, calling Salmonella serovar via SISTR with monophasic Typhimurium awareness, running Pangolin UShER mode with pangolin-data version pinning, or selecting a typing resolution to match the surveillance question.
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。
Automate Async Interview tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Autom tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Axonaut tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Ayrshare tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Atlassian tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Auth0 tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Autobound tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate Aryn tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。