983 件 ・ 関連度順
概要と使いどころ
Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.
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。
Scaffold the co-located feature structure in frontend/src. Use when creating a new page, feature, view (tab), or component folder, when a feature needs a shell with tabs, or when moving existing code out of src/container into src/pages. Generates the full folder tree (components/hooks/store/types/utils/constants/__tests__/README) and registers the page's routes with one command.
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 wants to run cognee with Docker or docker compose — trying it out from the prebuilt image, starting the API server in a container, or bringing up the full stack (UI, MCP, Postgres, Neo4j) with compose profiles.
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 local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when agents need to read attached Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, or text-based PDF files without uploading them to a hosted parser.
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。
Give chosen NanoClaw agents a real phone number as a container tool — the `dial` CLI baked into the agent image plus OneCLI credential injection for api.getdial.ai, scoped per agent, so the agents you pick can send SMS, place AI voice calls, and receive verification codes from inside the sandbox. Independent of the Dial channel; idempotent; re-run to change which agents may use it. Use when the user wants agents to text, call, or run `dial …` from a chat, without wiring Dial as a messaging channel.
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。
Finish migrating a NanoClaw v1 install into v2. Run after `bash migrate-v2.sh` completes. Seeds the owner, migrates legacy memory, reconciles container configs, and helps port custom v1 code. Triggers on "migrate from v1", "finish migration", "v1 migration".
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 OpenCode as an agent provider. OpenRouter, OpenAI, Google, DeepSeek, etc. via OpenCode config — not the Anthropic Agent SDK. Per group via `ncl groups config update --provider opencode`; host passes OPENCODE_* and XDG mount when spawning containers.
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 Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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 Atomic Chat MCP server so the container agent can call local models served by the Atomic Chat desktop app via its OpenAI-compatible API.
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 Vercel deployment capability to NanoClaw agents. Installs the Vercel CLI in agent containers and sets up OneCLI credential injection for api.vercel.com. Use when the user wants agents to deploy web applications to Vercel.
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。
Install rtk token-compression proxy into agent containers. Routes Bash tool calls through rtk for 60–90% token savings on dev commands (git, cargo, pytest, docker, kubectl, etc.).
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。
Health smoke tests + auto-fix for gbrain installs (and OpenClaw services when present). Run after machine/container restarts or whenever something seems broken. Tests critical services, auto-fixes bounded local issues, and reports worker topology without starting daemons. Extensible via user-defined test scripts in ~/.gbrain/smoke-tests.d/*.sh.
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。
FastGPT CI workflow 双轨同步。当用户修改或新增 .github/workflows/ 下的 GitHub Actions workflow 时必须触发：同步更新 .forgejo/workflows/ 对应文件保持功能一致，或判断是否需要新建 Forgejo 版本。涉及 CI、GitHub Actions、Forgejo Actions、镜像构建、container registry、artifact、workflow yaml 改动、build-* workflow、test-* workflow 时也使用此技能。即使用户只提到"改一下 CI"或"加个 workflow"也应触发。
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 you need to visually interact with a GUI: test buttons, fill forms, verify visual layouts, fuzz web pages, automate user flows, take screenshots, or perform end-to-end QA on any application. Works on cloud VMs, Docker containers, local machines, and sandboxes. Needs the `cua` CLI (curl -fsSL https://cua.ai/install.sh | sh).
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。
Zoom Meeting SDK Web - Component View. Embeddable Zoom meeting components with Promise-based API for flexible integration. Ideal for React/Vue/Angular apps and custom layouts. Uses ZoomMtgEmbedded with async/await patterns and embeddable UI containers.
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 context-mode tools (ctx_execute, ctx_execute_file) instead of Bash/cat when processing large outputs. Triggers: "analyze logs", "summarize output", "process data", "parse JSON", "filter results", "extract errors", "check build output", "analyze dependencies", "process API response", "large file analysis", "page snapshot", "browser snapshot", "DOM structure", "inspect page", "accessibility tree", "Playwright snapshot", "run tests", "test output", "coverage report", "git log", "recent commits", "diff between branches", "list containers", "pod status", "disk usage", "fetch docs", "API reference", "index documentation", "call API", "check response", "query results", "find TODOs", "count lines", "codebase statistics", "security audit", "outdated packages", "dependency tree", "cloud resources", "CI/CD output". Also triggers on ANY MCP tool output that may exceed 20 lines. Subagent routing is handled automatically via PreToolUse hook.
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 to capture a full-page screenshot, long screenshot, or complete page capture of a web page. Handles SPA scroll containers, lazy-loaded images, and very tall pages via Chrome DevTools Protocol with zero external dependencies.
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 DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.
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。
Remove multi-vendor AI provenance marks: invisible Unicode (Layer A), statistical text watermarks via rewrite (Layer B, always offer), and C2PA/EXIF/XMP/container metadata on PNG/JPEG/WebP/SVG/PDF/DOCX/ODT/HTML/MD/TEX. Covers Claude, Gemini/SynthID-class, OpenAI provenance, and open-LLM sampling marks. Use when the user asks to strip watermarks, remove C2PA/Content Credentials, clean AI metadata, remove invisible Unicode, anti-detect clean AI output, or runs /remove-ai-marks (aliases: /remove-claude-marks).
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: User wants to extend Docker with custom tools, personalize the Docker environment, or set up user-specific Docker customization. Triggers: 'extend docker', 'docker-extend', 'add tools to docker', 'customize docker', 'add my tools to the container', 'personalize docker setup', 'docker user setup', 'install tools in docker'. Does: Interactively sets up Dockerfile.user and docker-compose.override.yml so users can add personal tools to their Docker environment without affecting maintainer files or committing user-specific config to git.
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。
Explains why a process is running and what started it, using the witr CLI. Use when a port is already in use (EADDRINUSE), a dev server or other process was left running, an unknown or stuck process needs explaining, or you need to know which service, container, shell, supervisor or scheduled job started a process, holds a port or holds a file lock. Use it instead of chaining lsof, ps, ss, netstat and docker ps.
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 GKE Cloud TPU multi-slice training hangs (Megascale `HANG_DETECTED` logs and hang monitored events) using the ML Diagnostics `Megascale XLA (MXLA) Hang Analyzer` (`gcloud alpha mldiagnostics monitored-events`) and 1-minute Cloud Monitoring multi-slice latency metrics (`kubernetes.io/container/multislice/*`). Distinguishes XLA compiler/HLO launch divergence and host data-input stalls from TPU chip, SparseCore, ICI, or network fabric faults. Use when multi-slice TPU training jobs freeze without progressing steps, emit `HANG_DETECTED`, or stall in collective operations. Don't use for gradual step-time throughput drops without hangs (use gke-ai-troubleshooting-tpu-performance-degradation) or pod preemption/eviction restarts (use gke-ai-troubleshooting-jobset-interruption).
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。
Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.
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。
Diagnoses GKE persistent-storage failures — volume attach/mount errors (Regional PD on optimized VMs, fsGroup mount timeouts), disk-performance and node storage-pressure issues, slow-disk Pod-creation failures, volume-expansion problems, Local SSD / Hyperdisk Storage Pool creation errors, and Cloud Storage FUSE OOM. Use when Pods are stuck in ContainerCreating, volumes fail to attach or mount, or nodes report storage pressure. Don't use for routine storage provisioning or StorageClass/PVC authoring (see the gke-storage 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。