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概要と使いどころ
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。
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake 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 asks about a US-listed company or the US market and wants sourced numbers, such as SEC filings and what a 10-K or 10-Q says, income statements and balance sheets, earnings call transcripts, insider or congressional trades, 13F institutional holders, short interest, stock prices, option chains, stock screens or macroeconomic indicators. Calls the Equibles MCP 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。
Search the live web and read URLs through the You.com MCP server. Use when you need current information beyond training data: recent releases, docs, pricing, news, or any question where facts may have changed. Two endpoints: keyless basic search at https://api.you.com/mcp?profile=free, or full tools with an API key from https://you.com/platform/api-keys.
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 Ontoly's deterministic Software Graph and MCP server for codebase architecture, request tracing, dependency analysis, and impact analysis.
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。
Access DeFi data from DexPaprika: token prices, liquidity pools, OHLCV, transactions across 34+ blockchains and 30M+ pools. Free, no API key needed. Install MCP: add https://mcp.dexpaprika.com/sse as SSE server, or install plugin: /plugin marketplace add coinpaprika/claude-marketplace
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。
Access cryptocurrency market data from CoinPaprika: prices, tickers, OHLCV, exchanges, contract lookups for 12,000+ coins and 350+ exchanges. Free tier, no API key needed. Install MCP: add https://mcp.coinpaprika.com/sse as SSE server, or install plugin: /plugin marketplace add coinpaprika/claude-marketplace
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。
Fetch a real product's current price, stock, rating, or images from retailer pages over the Apify MCP server, and return them as typed fields rather than prose. Use when someone asks what a product costs right now, whether it is in stock, how it is rated, to compare a product across retailers, or to check a product URL they pasted. Also use when an agent would otherwise answer a product question from training data. Not for managing your own store's catalog, not for payments, and not for questions answerable without live retailer data.
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。
Performance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. Not for accuracy / RAGAS scoring (use rag-eval) or for deploying / repairing services (use rag-blueprint).
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 human users' AI agents to the NemoClaw docs MCP server and canonical Fern documentation in Markdown form. Use when users ask how to install, configure, operate, troubleshoot, secure, or learn NemoClaw with an AI coding assistant. Trigger keywords - nemoclaw docs, use nemoclaw with ai agent, nemoclaw mcp docs, nemoclaw install help, nemoclaw quickstart, nemoclaw markdown docs, llms.txt, agent 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。
Run and validate an end-to-end Mission Control showcase with a locally installed Isaac Sim launched in its GUI window, driven through the isaac-sim-remote Python server, with Nova Carter SIL. Use for demos, showcase replays, Mission Control driving a simulated robot, or diagnosing the integrated small-warehouse scenario. Detect existing Isaac Sim installations without modifying them, automatically select a usable runtime without prompting whenever compatibility can be confirmed, and delegate requested installation or version changes to isaac-sim-installation. Defaults to a canonical Isaac 6.1 warehouse and deterministic circular route when the user does not specify another scenario.
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。
Add EAGLE-3 or draft-model speculative decoding to a Jetson vLLM server when TPOT is the bottleneck.
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。
Operate NVIDIA DOCA Management Service on a BlueField, Arm/x86 host, or Kubernetes pod: from DOCA 3.5 the local `dms-cli` (one command per YANG path, no server), and the `dmsd` + `dmspe` service: choose deployment and authentication, configure `-allowed_users` and `dmsgroup`, use gNMI Get/Set/Subscribe, run supported gNOI workflows, and debug frontend/backend failures. Trigger even without "DMS" for "manage a remote BlueField over gRPC", "gNOI reboot from orchestrator", or fleet-management requests. SAFETY: reboot, OS install, factory-reset, and managed-file deletion are destructive and require target-bound explicit confirmation; never invoke them speculatively. Route installation and library/API build questions elsewhere, and route turnkey aggregation to the externally-productized DOCA Telemetry Service.
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。
DOCA Flow packet steering on NVIDIA NICs/DPUs, linked into a C application: match/action pipes, ports, representors, forwarding, hairpin, counters. Trigger on packet steering, classifier, rule-matching, representor, hairpin or 5-tuple-to-queue questions even when "DOCA Flow" is not named. Remote or non-C++ control over gRPC belongs to doca-flow-grpc-server. Also covers pipe validation before hardware programming, Flow/DOCA version match, and Flow API errors. First app: follow the local bundle (doca-setup, doca-programming-guide, doca-flow, doca-public-knowledge-map). Stage 1 pull nvcr.io/nvidia/doca/doca (NGC catalog tag, never invent); Stage 2 needs a real NIC. Then ls samples inside the container; never emit main.c, a Dockerfile, or hand-typed -l flags. Route software-only host pipelines, plain DPDK `rte_flow`, kernel TC, OVS, BFB bring-up, and DPU OS installation elsewhere. DPU OS installation is destructive and always requires explicit confirmation.
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 when the user is measuring GPU-kernel-initiated RDMA WRITE latency through doca-gpunetio — building and running the `gpunetio_ib_write_lat` client + server pair under `doca/tools/gpunetio_ib_write_lat/`, checking GPU-NIC pairing, reading the half-iter / full-iter / CUDA-side usec columns, characterizing median / p99 / jitter for a real-time control loop, picking GPUNetIO vs GPI vs CPU-initiated `perftest`, or weighing the latency-vs-batching trade-off. Trigger even without 'GPUNetIO' or 'ib_write_lat': 'GPU kernel RDMA latency benchmark', 'how fast can a CUDA kernel post a WRITE', 'p99 RDMA latency on H100 + ConnectX', 'kernel-launched WR tail latency', or 'compare GPU-init vs CPU-init perftest'. Route elsewhere for bandwidth runs (doca-gpunetio-ib-write-bw), the GPI surface (doca-gpi), library debugging (doca-gpunetio), or DOCA install.
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 when the user is building, running, or interpreting the doca/tools/gpunetio_ib_write_bw client+server benchmark — a CUDA kernel on the client posts RDMA WRITE work requests through the doca-gpunetio device-side surface to measure sustained GPU-driven WRITE bandwidth on a GPU+IB-device pair. Trigger even when the user does not explicitly mention "doca-gpunetio-ib-write-bw" or "GPUNetIO" — typical implicit phrasings include "measure WRITE BW when the GPU posts the WRs", "BW swings between runs on the same flags", "is the NIC saturated or am I CPU-bound on the CUDA kernel", "meson compile fails for the GPUNetIO bw tool", "nvidia_peermem isn't picking up my GPU buffer", or "GPU-initiated WRITE throughput vs CPU-initiated perftest". Refuse and route elsewhere for general doca-gpunetio library work, DOCA install, the GPU-initiated WRITE latency analog, the CPU-initiated upstream perftest, or application-level end-to-end throughput — those belong to other 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。
Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.
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。
Golang everyday observability — the always-on signals in production. Covers structured logging with slog, Prometheus metrics, OpenTelemetry distributed tracing, continuous profiling with pprof/Pyroscope, server-side RUM event tracking, alerting, and Grafana dashboards. Apply when instrumenting Go services for production monitoring, setting up metrics or alerting, adding OpenTelemetry tracing, correlating logs with traces, migrating legacy loggers (zap/logrus/zerolog) to slog, adding observability to new features, or implementing GDPR/CCPA-compliant tracking with Customer Data Platforms (CDP). Not for temporary deep-dive performance investigation (→ See `samber/cc-skills-golang@golang-benchmark` and `samber/cc-skills-golang@golang-performance` 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。
Golang package and module lookup via `godig`, a pkg.go.dev API client (CLI + MCP server). Use for any Go/Golang library's documentation, API signatures, symbols, usage examples, which versions exist, licenses, whether a dependency has CVEs, or who imports a package — prefer this over Context7 for any Go package or module. Read-only, no auth. Not for upgrading dependencies (→ See `samber/cc-skills-golang@golang-dependency-management` skill), choosing a library (→ See `samber/cc-skills-golang@golang-popular-libraries` skill), or local symbols and an already-used dependency's resolved source, call sites, and generic instantiations (→ See `samber/cc-skills-golang@golang-gopls` skill).
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。
Provides gRPC usage guidelines, protobuf organization, and production-ready patterns for Golang microservices. Use when implementing, reviewing, or debugging gRPC servers/clients, writing proto files, setting up interceptors, handling gRPC errors with status codes, configuring TLS/mTLS, testing with bufconn, or working with streaming 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。
Implements GraphQL APIs in Golang using gqlgen or graphql-go. Apply when building GraphQL servers, designing schemas, writing resolvers, handling subscriptions, or integrating GraphQL with existing Go HTTP services. Also apply when the codebase imports `github.com/99designs/gqlgen` or `github.com/graph-gophers/graphql-go`.
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。
[omh] Which tools and credentials a workflow needs: inventory which MCP servers, CLIs, APIs, credentials, and connectors a workflow needs; use external-connector-readiness to assess one named integration. Use when the user says: toolbelt-readiness, mcp readiness, tool readiness, plugin readiness, connector readiness, needed mcp, api credential, missing cli.
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。
[omh] Which tools and credentials a workflow needs: inventory which MCP servers, CLIs, APIs, credentials, and connectors a workflow needs; use external-connector-readiness to assess one named integration and executor-runtime-readiness to choose the coding owner. Use when the user says: toolbelt-readiness, mcp readiness, tool readiness, plugin readiness, connector readiness, needed mcp, api credential, missing cli.
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。
Query Fintel (fintel.io) institutional market data through its REST API or official MCP server. Use this skill whenever the user mentions Fintel or asks about short interest, short interest ratio or days to cover, short squeeze data, borrow rate or cost to borrow, shares available to borrow, daily short volume, fails-to-deliver (FTD), 13F institutional owners ("who owns X"), insider buying or selling from SEC Form 3/4/5, analyst price targets, ratings and forecasts, dividend or earnings history and calendars, EOD or last prices, security lookup by ticker, CUSIP, ISIN, or FIGI, Fintel leaderboards, or their Fintel watchlists and alerts. Read-only: GET endpoints 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。