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概要と使いどころ
End-to-end smoke against the local rembric dev server (`pnpm run dev`, host Next.js dev on :3000). Apply when the user says "smoke", "probar contra docker", "dev:up", or after applying an OpenSpec change that touches HTTP (`apps/web/src/app/api/`), MCP tools (`packages/mcp/src/`), or DB migrations (`packages/db/src/migrations/`). Encodes bring-up, readiness verification, probe pattern and teardown — not the probes themselves.
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。
Apply when creating, modifying, or reviewing any Rembric agent plugin. Triggers on changes under `apps/plugin/`, on new clients added alongside Claude Code / Codex CLI / Hermes Agent / opencode / Pi, on edits to `apps/plugin/mcp-bridge/`, `apps/plugin/bin/rembric-plugin-core.mjs`, per-client manifest changes, or plugin install/uninstall scripts. End-to-end validation against a local dev server (`pnpm run dev`, host Next.js on :3000) is mandatory whenever local testing is feasible.
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。
Search NCBI databases using Biopython Bio.Entrez (ESearch, EInfo, EGQuery, ESpell). Use when finding records by keyword, building reproducible field-qualified queries, navigating the Entrez Query Translator, exploiting the history server for large result sets, handling retmax caps, or interpreting weekly index lag. Covers PubMed, Nucleotide, Protein, Gene, SRA, GEO, Assembly, Taxonomy, ClinVar, dbSNP.
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。
Run remote BLAST searches against NCBI servers using Biopython Bio.Blast.NCBIWWW. Use when identifying unknown sequences, finding homologs, picking the correct BLAST program (blastn/blastp/blastx/tblastn/tblastx/psiblast/megablast/dc-megablast), interpreting Karlin-Altschul E-values, avoiding the max_target_seqs trap (Shah 2019), choosing composition-based statistics, or limiting searches by organism. Covers RID lifecycle, database choice (nt/nr/refseq_select/swissprot), word-size and CBS taxonomy.
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。
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.
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。
Search scientific papers via the BGPT MCP server and retrieve structured experimental data — methods, results, conclusions, quality scores, and 25+ metadata fields per paper.
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。
Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.
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 guide for Backend.AI distributed computing platform. Automatically activates when users ask about: - Backend.AI architecture, components (Manager, Agent, Storage Proxy, Webserver, App Proxy) - Features (session scheduling, Sokovan orchestrator, multi-tenancy, resource allocation) - APIs (REST, GraphQL), authentication, RBAC authorization - Container runtime (kernels, jail sandbox, hook library, virtual folders) - Accelerator support (CUDA, ROCm, TPU, NPU, Graphcore IPU) - Client SDKs (Python, Java, JavaScript, PHP) - Setup, requirements (Python 3.13+, Docker, PostgreSQL, Redis, etcd) - How WebUI connects to/interacts with Backend.AI backend - Plugin interfaces, development setup, infrastructure Use when user mentions "Backend.AI", "backend.ai", "Sokovan", component names, or asks about the backend platform this WebUI connects to. allowed-tools: WebFetch, Read
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 provides AWS cost optimization, monitoring, and operational best practices with integrated MCP servers for billing analysis, cost estimation, observability, and security assessment.
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 a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code for a project, or wants to know what Claude Code features they should use.
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。
Drift check between the baseline implementation on disk and the claims in `docs/init/seed.md` + cross-references in CLAUDE.md, README.md, and the rendered docs site. Verifies hook/agent/skill/command names + counts, settings.json wiring, project.json key presence, .mcp.json servers, vendored license files, and helper script presence. Exit 0 PASS / 1 FAIL — suitable for CI. Read-only; safe to invoke any time.
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。
MCP client: connect servers, register tools (stdio/HTTP).
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 architecture diagrams with draw.io in headless/server environments (WSL2, VPS, Docker)
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。
⚠️ DEPRECATED: This SDK has been renamed to Call Automation. For new projects, use azure-communication-callautomation instead. This skill is for maintaining legacy code only.
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 server-side call automation workflows including IVR systems, call routing, recording, and AI-powered interactions.
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。
Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.
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 a user wants a standalone browser-based visual companion for interactive mockups, diagrams, wireframes, layout comparisons, visual brainstorming, or clickable visual option selection. Starts a local zero-dependency Node server, writes HTML screens, and reads browser click events.
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 or modify backend APIs, services, jobs, persistence, and integrations while preserving contracts, authorization, data integrity, and failure behavior. Use for server-side features, database changes, background processing, backend defects, and service refactors; do not use for frontend-only or infrastructure-only 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。
Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.
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。
FiveM RP server engineering for QBCore, ESX.
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 and manage trusted local Paseo plugins. Use when the user asks to create, edit, install, reload, enable, disable, remove, or troubleshoot a Paseo plugin; add lifecycle hooks; transform agent configuration, environment, MCP servers, or workspace creation; automate permissions or turn follow-ups; add a screen, sidebar header or footer item, or workspace panel; add Command Center items or slash commands; add composer pills or attachment sources; transform, render, or append agent timeline items; contribute a theme; use Paseo from plugin code; or add plugin RPCs.
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 relational database schemas (and choose when to go NoSQL) that stay maintainable and fast. Use this skill whenever the user mentions tables, DDL, entities and relationships, normalization (1NF/2NF/3NF), primary and foreign keys, UUID vs bigint IDs, indexes (B-tree, composite, covering, partial), EXPLAIN, constraints (CHECK, UNIQUE, exclusion), transactions and isolation levels, migrations (Alembic, Prisma, Flyway, expand-contract, backfilling), or SQL vs NoSQL (MongoDB, DynamoDB, Cassandra, graph databases). Also trigger for "design the database", "model this domain", "which database should I use", or writing ORM models and migration files for PostgreSQL, MySQL, SQLite, or SQL Server.
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 local Apple Music MCP server to browse or manage the user's library and playlists, search the catalog, discover music, control playback, or edit the Up Next queue. Trigger whenever the user asks about their Apple Music account, listening history, playlists, library, playback, recommendations, or queue.
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。
Measure, root-cause, fix, verify and record performance contention on a developer machine: cloud-sync daemons (iCloud Drive, OneDrive, Dropbox, Google Drive), file indexers, AI-tool MCP server fleets, and automation browsers left behind by tests and browser skills. Trigger when the machine is slow, apps freeze, browser or MCP tool calls time out, load exceeds the core count, or before and after any UI/UX/performance test run. Includes the L0–L4 optimisation scale and the test-hygiene contract.
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。