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概要と使いどころ
Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
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。
Compatibility alias for OpenAI platform documentation guidance. Delegate to the canonical local `openai-docs` payload while preserving route compatibility.
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 should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service 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。
Remove AI-generated code slop from a branch: unnecessary comments, redundant defensive checks, boilerplate, style drift, and type casts. Use for cleanup of AI-written code, not for broad code review, security audit, TDD, or final 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。
Investigate outliers, rare events, spikes, and suspicious records in datasets. Use as an explicit anomaly-analysis helper when you want concrete anomaly-detection workflow guidance, not generic data validation or end-to-end ML ownership.
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。
Make a website's team or about page photos look like one set — scan the headshot folder locally, flag photos whose aspect ratio, brightness, colour temperature, background or resolution differ from the rest, write a shared photo spec, and optionally export every photo at the same crop and size. Use when building or fixing a team page, "our team photos look inconsistent", "make all headshots the same size", "standardize staff photos", or when adding a new hire's photo to an existing page. Uses the free ProfessionalHeadshot.io MCP for framing guidance and photo scores when connected; the local scan works without it.
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 AI design contract (AI-SPEC.md) for phases that involve building AI systems — framework selection, implementation guidance from official docs, and evaluation strategy
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。
Turn a photo into a specific AI look (new hairstyle, collectible figurine, royal pet portrait, wedding photo, 90s yearbook, sticker, HD restore) or a photo into a dance video, using Kavel (www.kavel.ai). Use when the user wants to restyle/transform a photo, asks "how do I make an AI X from my photo", or wants a photorealistic image edit that keeps the same face. Gives the right tool, a model-tuned prompt, and the generate link.
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。
Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.
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。
Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor, scatter_tensor, domain parallelism, sequence/spatial sharding, ring attention, DeviceMesh + DDP/FSDP2 hybrid parallelism, or physicsnemo.domain_parallel. Do NOT use for generic PyTorch DDP/FSDP setup without domain parallelism, picking a PhysicsNeMo model or example (use physicsnemo-discover), or non-distributed training questions.
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。
Brev instance operating guidance for NeMo-RL agents working in /home/ubuntu/RL with limited workspace disk, a larger /ephemeral volume, and optional /home/ubuntu/RL/.env secrets. Use when running nemo-rl-auto-research campaigns, experiments, training jobs, model or dataset downloads, shared cache-heavy commands, log-producing runs, checkpoint generation, W&B or Hugging Face authenticated workflows, or any workflow that may create large files on Brev.
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。
Practical guidance for training MoE VLMs in Megatron Bridge. Compares FSDP and 3D-parallel approaches, using rounded lessons from Qwen3-VL, Qwen3-Next, and other multimodal experiments.
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。
Long-context MoE training guidance for Megatron Bridge. Covers CP sizing, selective recompute, dispatcher choices, and practical patterns from DSV3, Qwen3, and Qwen3-Next long-context experiments.
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。
Not for writing library code (name that library skill). Use this skill whenever another DOCA skill says "prefer the structured tool per doca-structured-tools-contract", or when the user wants a one-shot answer that consolidates info multiple manual commands would produce — DOCA env / version / devices / capabilities / validate / host vs DPU state. Trigger even when the user does not explicitly mention "structured tool" or "doca-env --json" — typical implicit phrasings include "is there one command that tells me everything about my DOCA install", "what version is X capability available since", "every PF/VF/SF visible on this BlueField with PCIe address", "will this pipe pass validate before commit", "diff host vs DPU state", or "why does the agent give a one-line answer on host A and five commands on host B". Refuse and route elsewhere for general DOCA orientation, specific library API how-to, or install-from-scratch guidance — those belong to the per-library skill, doca-public-knowledge-map, or doca-setup.
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。
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
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 for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance.
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。
Contextual guidance and command discovery. Three modes — narrative (first-time), contextual (mid-task), compact (quick reference). Shows available commands, active skills, and intelligent suggestions based on vault state. Triggers on "/help", "what can I do", "show commands", "how does this 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。
Idiomatic Golang design patterns — functional options, constructor APIs, `init()` and global-state avoidance, enums, panic vs error decisions, resource management and lifecycle, graceful shutdown, timeouts and retries, streaming and iterators, and architecture styles (clean, hexagonal, DDD, flat). Apply when choosing between architectural patterns, implementing functional options, designing constructor APIs, setting up graceful shutdown, applying resilience patterns, or asking which idiomatic Go pattern fits a specific problem. Not for wiring a DI container or comparing DI libraries (→ See `samber/cc-skills-golang@golang-dependency-injection` skill), nor for error wrapping, `errors.Is`/`As`, or logging mechanics (→ See `samber/cc-skills-golang@golang-error-handling` 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。
Golang ecosystem watch list — official sources (go.dev/blog, pkg.go.dev, tour.golang.org, golang-nuts), newsletters (Golang Weekly, Awesome Go Newsletter), communities (r/golang, gophers.slack.com, Go Forum, go.dev/wiki), blogs (Dave Cheney, Ardan Labs, Rob Pike), YouTube channels (Gopher Academy, GopherCon EU/UK), conferences, and Go contributors to follow on GitHub, X and Bluesky. Use when seeking Golang learning resources, discovering new libraries or tools, finding community channels or meetups, picking Go people to follow, or keeping up with Go language changes and releases. Not for querying a specific module's versions, docs, or vulnerabilities from the CLI (→ See `samber/cc-skills-golang@golang-pkg-go-dev` 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。
Fetch normalized stock sentiment across Reddit, X.com, financial news, and Polymarket from the Adanos Finance API: buzz score, bullish percentage, mention or trade counts, and trend. Use this skill whenever the user asks how much a stock is being discussed or how hot it is on social platforms, how many Reddit mentions or Polymarket bets a company has, whether Reddit, X, and news agree, or wants to compare stock buzz and sentiment across tickers. Read-only: it never places trades or modifies anything.
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] Deep dive before a decision: deep research engine - grounding for specs and decisions: study open-source reference implementations with pinned refs, gather live web evidence with citation discipline, verify contested claims, and distill a decision-grounding dossier that planning consumes; for a decision brief use research-brief, for upstream guidance use web-research. Use when the user says: research plan, literature review, research literature, review recent papers, deep research, deep-research, exhaustive research, saturation research.
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] Turn repeated lessons into written rules: extract repeated principles from skills, prompts, traces, reviews, and failures into reviewed rule candidates without auto-mutating guidance. Use when the user says: rules-distill, rules distill, distill rules, rule distillation, principle distill, skill principles, extract agent rules, turn traces into rules.
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] Scattered knowledge needing a wiki: wiki construction blueprints and retained knowledge capture with destination-aware external knowledge connection guidance. Use when the user says: wiki, project wiki, build a wiki, start a wiki, organize my notes, external knowledge store, knowledge base, Obsidian.
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] Choosing among OMH skills for a request: router guidance for using oh-my-hermes workflow skills inside Hermes Agent.
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。