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概要と使いどころ
API migration strategies, deprecation workflows, and header/URL/content versioning. Activate on: API versioning, backward compatibility, deprecation, breaking change, API migration, v1 v2, sunset header. NOT for: schema evolution in data (use schema-evolution-manager), gateway routing (use api-gateway-reverse-proxy-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 in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).
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。
Project gene annotations across genomes using TOGA (Kirilenko 2023 whole-genome-alignment chain-based projection with intactness classification), CESAR 2.0 (Sharma, Schwede & Hiller 2017 codon-aware exon projection), LiftOff (Shumate & Salzberg 2021 reference-based annotation transfer), Liftover (UCSC), GeMoMa (Keilwagen 2019 evidence-based projection), and Comparative Annotation Toolkit (CAT). Use when transferring annotations from a well-annotated reference to query genome(s), classifying gene-loss vs gene-intact across many genomes at scale, building Zoonomia-style comparative annotations across hundreds of mammals or birds (Kirilenko 2023), detecting pseudogenization, projecting alternative isoforms, or selecting between WGA-anchored (TOGA) vs ortholog-based (LiftOff) annotation transfer strategies.
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。
Prepares statistical reports for clinical trials following CONSORT 2025, SPIRIT 2025, ICH E9(R1) estimands, and FDA 2023 covariate adjustment guidance. Covers Table 1 generation, analysis populations (ITT/FAS/PP/Safety), the 5 ICH E9(R1) intercurrent-event strategies, MMRM under MAR (mmrm), reference-based MI (rbmi J2R/CR/CIR), Permutt tipping-point sensitivity, and Rubin's-rules vs frequentist variance debate. Use when preparing regulatory submissions, defining estimands, or implementing missing-data sensitivity analyses.
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。
Comprehensive backend development guide for Langfuse's Next.js 14/tRPC/Express/TypeScript monorepo. Use when creating tRPC routers, public API endpoints, BullMQ queue processors, services, or working with tRPC procedures, Next.js API routes, Prisma database access, ClickHouse analytics queries, Redis queues, OpenTelemetry instrumentation, Zod v4 validation, env.mjs configuration, tenant isolation patterns, or async patterns. Covers layered architecture (tRPC procedures → services, queue processors → services), dual database system (PostgreSQL + ClickHouse), projectId filtering for multi-tenant isolation, traceException error handling, observability patterns, and testing strategies (Jest for web, vitest for worker).
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 and manage database migrations with reversible changes, proper naming conventions, and zero-downtime deployment strategies. Use this skill when creating database migration files, modifying schema, adding or removing tables/columns, managing indexes, or handling data migrations. Apply when working with migration files (e.g., db/migrate/, migrations/, alembic/, sequelize migrations), schema changes, database versioning, rollback implementations, or when you need to ensure backwards compatibility during deployments. Use for any task involving database structure changes, index creation, constraint modifications, or data transformation 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。
Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.
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 Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning
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 in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.
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。
Setup and optimize cryptocurrency mining operations — AI-powered mining (soul.md protocol), parallel agent deployment, accumulation strategies, and performance 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。
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
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。
Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com.
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。
Explore open-source GitHub repository source trees via web browsing to analyze and compare feature implementations at the code level. Supports two modes: cross-project comparison and single-project deep dive. Use when evaluating how OSS projects implement a specific feature, choosing architecture patterns, or benchmarking implementation strategies.
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 has merge conflicts or says "resolve conflicts". Understands conflict markers, resolution strategies, and verification 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。
Use when optimizing application performance — caching strategies, eager loading, query optimization, Redis patterns, or background job design.
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 working with Laravel queues in production — Horizon dashboard, worker supervision, job metrics, balancing strategies — even when the user just says 'my jobs are piling up'.
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 designing monitoring dashboards — visualization selection, layout principles, observability strategies (RED/USE/Golden Signals), and data storytelling.
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 working with database architecture, MariaDB/MySQL tuning, indexing strategies, slow queries, or multi-connection patterns — even when the user just says 'this query is slow'.
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。
Guidelines and strategies for constructing meaningful test suites, property-based tests, metamorphic relations, and fuzzing harnesses. Trigger when: - Designing verification bounds, writing tests, creating test invariants, or implementing validation gates. - Prompt contains: testing, test design, property-based testing, PBT, metamorphic testing, fuzzing, integration tests, E2E.
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。
Competitive positioning diagnostic — figures out where you actually stand relative to competitors and whether that position is defensible. Use this skill when someone needs to understand their real competitive position (not the one on the slide deck), when a new competitor has entered the market, when customers are switching and nobody can explain why, when pricing power is eroding, when a strategic investment depends on knowing whether the moat is real, or when leadership says "we're differentiated" but can't explain how. Draws on Playing to Win, Porter's generic strategies, and Blue Ocean thinking — applied as diagnosis, not planning. Based on practice by Eterdis (eterdis.com).
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 Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service layer classes with CRUD operations, partition key strategies, parameterized queries, or TDD pattern...
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。
Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.
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。
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews 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。
Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning Use when: adding search to, algolia, instantsearch, search api, search functionality.
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。