Build tools expert including Vite, Webpack, and bundler 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。
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Build tools expert including Vite, Webpack, and bundler 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。
Build AI agents using the Claude Agent SDK. Covers query functions, ClaudeSDKClient, custom tools, MCP servers, hooks, permissions, subagents, and browser control (Chrome extension, dev-browser skill). Use when creating agents, adding tools, configuring agent behavior, or automating browser 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。
Design, build, refactor, or review terminal interfaces—full-screen TUIs, interactive prompts, and command-line tools. Use for terminal-app layout and UX, CLI behavior, ncurses-style tools, dashboards, REPLs, fzf-like pickers, and libraries such as Bubble Tea, Ratatui, Textual, or Ink, including requests that name a known TUI such as lazygit, k9s, btop, helix, or yazi instead of saying “TUI.” Do not use for browser or web UI, native GUI, editor or font configuration, or backend and shell work that has no terminal interface.
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。
フロントエンドの動作確認。起動中サーバーを自動検出し、Chrome DevTools で操作・デバッグ・パフォーマンス分析を実行。
Preserve and conserve library and archival materials. Covers environmental controls (temperature, humidity, light), handling procedures, book repair techniques (torn pages, loose spines, foxing), acid-free storage, digitization for preservation, and disaster recovery planning. Use when establishing preservation practices for a new or existing collection, when materials show signs of deterioration, when setting up environmental controls for storage, when planning digitization to preserve fragile originals, or when creating a disaster recovery plan for a library or archive.
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。
Implement electronic signatures compliant with 21 CFR Part 11 Subpart C and EU Annex 11. Covers signature manifestation (signer, date/time, meaning), signature-to-record binding, biometric vs non-biometric controls, policy creation, and user certification requirements. Use when a computerized system requires legally binding electronic signatures for GxP records, when replacing wet-ink signatures in regulated workflows, when implementing batch release or document approval workflows, or when a regulatory gap reveals missing signature controls.
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。
Set up systematic data labeling workflows using Label Studio or similar tools. Implement quality controls, measure inter-annotator agreement, manage labeler teams, and integrate labeled data into ML training pipelines. Use when starting a supervised ML project that requires labeled training data, when model performance is limited by insufficient labeled examples, when labeling text, images, audio, or video, or when implementing active learning to prioritize the most valuable examples.
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。
Containerize an R-based MCP (Model Context Protocol) server using Docker. Covers mcptools integration, port exposure, stdio vs HTTP transport, and connecting Claude Code to the containerized server. Use when deploying an R MCP server without requiring a local R installation, creating a reproducible MCP server environment, running MCP servers alongside other containerized services, or distributing an MCP server to other developers.
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 a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.
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 AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add tools/capabilities, defer capability loading, stream output, define agents from YAML, or test agent behavior.
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。
Before committing any non-trivial change, dispatch the diff to a reviewer runtime via ATO (`ato dispatch <reviewer> --session <id>`), parse the numbered/severity-tagged findings, apply or defer each one with a recorded justification, then commit. Fights the "build passes therefore ship it" failure mode — what Garry Tan calls the AI agent complexity ratchet. Place in the v2.16 stack: this skill is the LAST gate. `ato-warroom` decides the design; `ato-mission` runs the multi-step work and produces the diff; `ato-review` checks the diff before commit. When the review is part of a Mission, dispatch the review with `--require-tools read_file,grep,git_diff,git_log` so the reviewer can walk the source itself instead of reasoning from a paraphrase (PR-1.5 tool surface). Receipts land in `execution_logs` and the Mission narrative. Fires automatically before commits touching public surface (CLI subcommands, Tauri commands, MCP tools, schema migrations, security boundaries) or whenever a diff exceeds ~50 LOC of behavior change.
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。
Forge a tool, connect an MCP server, or chain tools in one script.
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。
Go code refactoring with automated tools: gofmt -r, gopatch, and rsc.io/rf. Use this skill when performing mechanical rewrites across a codebase — renaming identifiers, migrating API calls, moving types between packages, rewriting expressions, or replacing deprecated patterns. Triggers when the task involves bulk code transformation, API migration, structural rewrite, or the user mentions gofmt -r, rf, gopatch, coccinelle-style patching, or large-scale rename/move in 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。
Run the Upstash CLI (`upstash`) from a terminal, shell script, or CI job when no Upstash MCP tools are in the session. Do not load this skill when Upstash MCP tools are available (the Upstash plugin registers mcp.upstash.com) - they already cover creating, listing, renaming, and deleting Redis databases, running Redis commands, usage stats, backups, Vector and Search indexes, QStash schedules and messages, Blob buckets, and Box, so call them directly. Use this skill for shell work the MCP does not do - a CI step or provisioning script that needs `upstash` commands with JSON output, piping results into other commands, `upstash auth login` and API-key setup, team and member management, changing plans, regions, TLS, eviction, auto-upgrade, or budgets, minting temporary S3 credentials for a Blob bucket, connecting a coding agent to Upstash with `upstash setup` (the Upstash plugin, or the remote MCP server plus skills), or when the user explicitly asks for the CLI or for managing Upstash without the console.
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 GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"
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 tool-use patterns for AI agents. TRIGGERS - Use when user needs help with ai-agent-tools related 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。
Build Solana trading and intelligence applications combining OKX DEX aggregation with Helius infrastructure. Integration-only layer — describes when and how to compose OKX tools with Helius tools for swaps, token discovery, smart money signals, meme token analysis, and portfolio intelligence.
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 Solana trading and intelligence applications combining OKX DEX aggregation with Helius infrastructure. Integration-only layer — describes when and how to compose OKX tools with Helius tools for swaps, token discovery, smart money signals, meme token analysis, and portfolio intelligence.
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。
chrome-devtools-mcp launcher — a single bash script that resolves Playwright's bundled Chrome-for-Testing and Node.js directly through Nix. See repo README for usage, override mechanisms, and version 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。
Use this skill when the user needs Obsidian runtime debugging or developer introspection through official desktop Obsidian CLI developer commands, including devtools, console/errors capture, DOM/CSS inspection, screenshots, CDP calls, and controlled eval. Do not use for regular note CRUD, task/property editing, Sync/Publish administration, or community tooling outside the official 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。
Use this skill when the user wants local Obsidian note or metadata work done primarily through documented official desktop `obsidian` CLI commands, with limited local vault filesystem support when needed for parent folders, path checks, ambiguity resolution, verification, or safe vault structure operations. Best for local vault search, note reads, exact-path note updates, backlinks, tasks, properties, templates, and local history. Do not use it for runtime admin, devtools diagnostics, workspace/navigation administration, community tools, `obsidian://` launcher tasks, Headless Sync or Publish workflows, or plugin-specific APIs.
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。
A 15-minute guided setup that teaches Cowork who you are, how you work, and what tools you use — so every result feels tailored instead of generic. Use when setting up Cowork for the first time, for personalizing your workspace preferences, during onboarding after your first session, when configuring your tools and context, or when the user says "set up cowork", "configure cowork", "why is cowork giving me generic results", "cowork setup", "personalize cowork", "make cowork know me", "cowork feels like chatgpt", or "how do I get better results from 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。
Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks 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。
Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
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。