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Claude Codeのファイル編集時に、Planktonで自動整形とコード検査を行う設定を支援するスキル。残った違反の自動修正や再検査、検査ルールの保護も扱います。

• 編集のたびに整形・コード検査したいとき
• 残った検査違反の自動修正を設定
• 検査設定のルール緩和を防ぎたいとき

外出先のスマートフォンやノートPCから自宅ネットワークへ接続するため、WireGuardのサーバー構築、端末ごとの鍵生成、通信経路の設定と接続不良の確認を支援します。

• 外出先から自宅のNASへ接続したいとき
• WireGuardサーバーを構築したいとき
• VPNに通す通信を選びたいとき

Claude Codeのセッション終了時に、エラー解決や修正から再利用できる手順を抽出・保存する旧版スキル。現在は非推奨で、既存環境の互換性確認や仕組みの参照向けです。

• 旧版のセッション終了時設定の確認
• 抽出基準や対象分類の調整
• 保存された学習スキルの見直し

AIエージェントの導入やモデル設定、外観変更、機能拡張を案内するスキル。Hermes Agentを複数の画面やメッセージサービスで使うための運用を支援します。

• 導入とモデル選択を進めたいとき
• メッセージサービスとの接続
• テーマや画面の拡張を行いたいとき

Set up Browser Use Cloud payments with x402 — pay per request from a crypto wallet (USDC on Base mainnet), no signup or API key. Two setups it works out up front — "just use it" (set up a wallet so you or Claude Code can run cloud browser tasks paid from the wallet — Claude writes and runs throwaway scripts, nothing touches your codebase) or "build it in" (install the SDK and write the key + code into your project). Walks through wallet setup, funding, .env, and a ~$1 test run. Use when the user asks about x402, pay-per-use, USDC payments, or wants Browser Use Cloud without an API key. For the free-tier signup (reverse-CAPTCHA → API key), use `browser-use cloud signup` or the `cloud` skill instead.

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 initial setup, configure global CLI settings, manage environment variables, check for updates, and configure autostart via the CLI setup and config commands.

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。

Any explicit Muse Code setting question or change (model, reasoning effort, /settings) requires a silent read_skill call for bundled:manage-settings as FIRST ACTION—no assistant text or other tool first. Never use for repository, app, eval, or other non-Muse configuration.

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。

Guided Cowork setup — install a matching plugin, try a skill, connect tools. Use when: set up cowork, setup cowork, get started with cowork, cowork onboarding, configure cowork, personalize cowork.

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。

Performs pathway and gene-set enrichment analysis on gene lists or ranked gene data and interprets the results. Used when the user has a set of genes (differentially expressed genes from PyDESeq2/Scanpy, CRISPR-screen hits, cluster marker genes, proteomics hits) and wants to know which biological pathways, GO terms, or gene sets are over-represented or enriched. Covers over-representation analysis (ORA / Enrichr / Fisher / hypergeometric), ranked Gene Set Enrichment Analysis (GSEA / preranked), single-sample scoring (ssGSEA/GSVA), and functional profiling via gseapy, g:Profiler, Enrichr libraries, MSigDB, GO, KEGG, Reactome, and WikiPathways — plus gene-ID mapping, choosing the right background universe, multiple-testing correction, redundancy reduction, dotplots/enrichment maps, and publication-ready tables. Use this for "pathway analysis", "enrichment analysis", "GO enrichment", "KEGG/Reactome pathways", "GSEA", "over-representation", "functional annotation", or "what pathways are my genes in".

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, update, and manage GitHub issues using MCP tools. Use this skill when users want to create bug reports, feature requests, or task issues, update existing issues, add labels/assignees/milestones, manage repository labels, set issue fields (dates, priority, custom fields), set issue types, manage issue workflows, link issues, add dependencies, or track blocked-by/blocking relationships. Triggers on requests like "create an issue", "file a bug", "request a feature", "update issue X", "set the priority", "set the start date", "create a label", "rename a label", "list repo labels", "link issues", "add dependency", "blocked by", "blocking", or any GitHub issue management task.

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。

Claude as the trainer. Walks an SMB owner through connecting their first two tools, runs one recipe to prove immediate value, interviews them about their business (industry, size, top three headaches), stores that context persistently so every other skill benefits, and sets a weekly check-in cadence. Use when the owner is getting started or says any of: "set me up," "setup," "help me get set up," "get started," "help me get started," "get me started," "what can you do," "I'm new to this," or is in their first session.

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。

Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".

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。

Analyzes the downstream impact (blast radius) using data lineage on Google Cloud when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset. - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset. Don't use for: - General BigQuery querying or data analysis (use BigQuery-related tools instead). - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage. - Creating or modifying lineage links directly.

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 JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster creation, basic workload deployment, or non-JobSet application issues.

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 developers through client library installation and authentication setup steps for the Data Manager API. Use this skill when a user is getting started with the Data Manager API and needs to setup their local environment, install the client library, or setup access to the API. Don't use for implementing audience or event ingestion logic (use the data-manager-api-audience-ingestion or data-manager-api-event-ingestion skills instead).

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 and onboard a user into LifeOS — the Life Operating System (current state → ideal state via TELOS + the Algorithm). The agentic installer detects your OS + harness, wires hooks with permission, scaffolds your USER tree, pulls in sources you provide, and runs the TELOS / current→ideal interview that seeds your Pulse dashboard. USE WHEN install LifeOS, set up LifeOS, lifeos setup, lifeos-setup, lifeos interview, onboard me, run the interview, integrate LifeOS into my harness, update LifeOS, uninstall LifeOS, first-time setup, lifeos doctor, check my install, what capabilities are broken. NOT FOR building or cutting a LifeOS release (private release tooling), editing TELOS after onboarding (use Telos / Interview), or LifeOS system maintenance (use the private maintenance 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。

Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".

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 the user's real desktop apps and windows on macOS, Windows, or Linux. Use when the user asks to open or drive a native app, click or type in a desktop UI, inspect or arrange a window, use their signed-in system browser, or verify an end-to-end GUI flow, including "open Settings and turn on dark mode", "click Save in that window", "what's on screen". Uses an accessibility-first driver (Cua Driver by default, Peekaboo on macOS). Not for Superset's in-app browser pane, headless scraping, or anything an API or CLI can do directly.

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。

First-pass triage of a possible production incident for Superset's hosted services. Gathers signals (recent deploys, Sentry spikes, health checks), proposes a severity and a status.superset.sh message, then stops for human approval. Use when someone reports an outage, errors spike, or asks "is something down?".

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 recurring chore into a Superset automation. Drafts the agent prompt, confirms the schedule or event trigger and the target, creates it with the CLI, and reviews the first run together. Use when the user wants a scheduled or recurring agent, a daily or weekly job, or an agent that reacts to a Slack message, GitHub pull request, Linear issue, Sentry issue or incoming email, or says things like "every morning do X", "automate this", "set up a cron agent", "run this on a schedule", "when someone opens a PR, do X".

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。

Controls the traffic-light actors on a running CARLA server — set a light green/red/yellow/off, freeze all lights (optionally all-green), set phase timing (green/yellow/red durations), and reset to the normal cycle. Target all lights, one by id, all in a junction, or the nearest. Use when the user asks to "make the light red", "freeze all lights green", "change the light timing", "turn the traffic lights off", or "reset the lights". This is the light actors, not the Traffic Manager (that's control-traffic).

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。

Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-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。

Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".

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。