2,456 件 ・ 関連度順
概要と使いどころ
Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management. Makes interfaces robust and production-ready. Use when the user asks to harden, make production-ready, handle edge cases, add error states, or fix overflow and i18n 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。
Add moments of joy, personality, and unexpected touches that make interfaces memorable and enjoyable to use. Elevates functional to delightful. Use when the user asks to add polish, personality, animations, micro-interactions, delight, or make an interface feel fun or memorable.
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。
管理会計ナビゲータースキル。ユーザーの相談内容を管理会計12領域に自動分類し、 適切な分析手法・実行スキルへルーティングする。予実差異分析、CVP分析、原価管理、 KPI設計、月次決算早期化など、管理会計の全領域をカバーする入口として機能。 COSO/IMA管理会計フレームワークに準拠。日英両言語対応。 Use when: ユーザーが管理会計に関する質問・相談をしたとき、どの分析手法を使うべきか 判断する入口として使用。「予算と実績の差が大きい」「原価を下げたい」「損益分岐点を知りたい」 などの相談を適切なスキルへ誘導する。 Triggers: "管理会計", "予実差異", "原価計算", "損益分岐点", "CVP", "KPI設計", "月次決算", "内製外注", "make or buy", "標準原価", "配賦", "ABC", "management accounting", "budget variance", "cost accounting", "break-even"
Convert Markdown documents to PDF. Two modes available — (1) Playwright-based conversion with Mermaid diagram support for technical documentation, and (2) fpdf2-based professional PDF generation with cover pages, themed styling, and business-quality table formatting for estimates, proposals, and reports. Use this skill when converting Markdown to PDF, generating business documents from Markdown, or converting Mermaid diagrams to images. Triggers on short phrases like "PDFに変換して", "markdownをpdfにして", "PDFにして", "PDF化して", "PDF出力して", "convert to PDF", "make a PDF", or any request involving converting content to PDF format.
AI（LLM）が生成した日本語テキストの「AI臭」を検出・診断し、人間らしい文章にリライトするスキル。 Use when: 「AIっぽい文章を直して」「人間らしくリライトして」「AI臭を消して」「この文章をもっと自然にして」 「テキストのAI感を減らして」「機械っぽさを取りたい」 "make this sound more human", "remove AI tone", "humanize this text", "detect if this is AI-generated". 6つのAI特有パターン（視覚的マーカー、単調なリズム、マニュアル的構成、非コミット姿勢、抽象語の濫用、 定型メタファー）を正規表現ベースで検出し、0-100のAI臭スコアを算出。3つの人間化技法 （バランスを崩す・客観を崩す・論理を崩す）でリライトを実行する。 Note: 検出スクリプトは日本語テキスト専用。英語テキストの場合はClaude自身がreferences/を参照して分析・リライトする。
Embedded firmware setup: STM32, ESP32, AVR, RP2040, Nordic nRF, Zephyr/RTOS, vendor SDKs, CMake/CMakePresets, VS Code/clangd, cross toolchains, flash/debug, Docker/CI. Use for MCU scaffolds, existing firmware modernization, BSPs, linker/startup files, SDK package selection, and embedded CI; prefer cpp-project-setup for host-side C++.
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。
Modern C++ project setup: CMake/CMakePresets, vcpkg, Ninja, VS Code/clangd, GoogleTest, clang-format/tidy, Doxygen, CI, macOS/Linux/Windows. Use for bootstrapping or modernizing host-side C++ apps and libraries; prefer embedded-project-setup for MCU firmware and cross-debug flows.
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。
Systematically rewrites AI-generated or AI-sounding text on web pages, documents, or pasted content to sound human. Use this skill whenever a user asks to "humanize", "de-AI", "make this sound less like AI", "rewrite to avoid AI detection", or "clean up AI writing". Also trigger when a user pastes text and asks to make it sound more natural, more human, or less robotic. The skill applies a strict deterministic rule pipeline — NOT creative rewriting — making it safe for agentic/automated use.
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 or audit an `/llms.txt` file at the site root that makes the site legible to LLMs and AI answer engines at inference time, following the llms.txt proposal (Jeremy Howard, 2024). Use this skill whenever the user asks to "build llms.txt", "create llms.txt", "generate llms.txt", "audit llms.txt", "make my site LLM-friendly", "expose the site to AI assistants", "let ChatGPT / Claude / Perplexity cite my site", "add an AI assistants index", or asks about `.md` companion pages for LLM consumption. Output is a valid `llms.txt` file (or an audit) plus optional `.md` companion page generation for top pages.
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 use the official AI Logo Maker package, pinned by digest, for paid hosted work on the Beatra 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。
Generate paid-ad image assets from a validated creative brief and brand profile using an explicitly configured image provider. Triggers on: generate ads, generate ad images, create ad creatives, create ad images, make ad images, generate visuals, make campaign visuals, generate images from campaign brief.
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 professional, visually excellent presentation slides in Marp Markdown format. Use this skill when the user asks to: - Create a presentation, slides, deck, slideshow, or プレゼン / スライド - Write or generate slides about a specific topic - Make a Marp .md file for presenting Produces complete, ready-to-render .md files with embedded custom CSS theme, narrative structure, and polished visual design. Supports Japanese and English content.
Use when the user wants to humanize text, make writing sound less like AI, or rewrite content to feel more natural. Triggers on "humanize", "make it sound natural", "too robotic", "sounds like AI", or similar. Works in Hebrew and English. Always output only the rewritten text — no explanations.
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 any markdown into a shareable web page via md.page. Use when the user asks to "share this", "publish this markdown", "create a shareable link", "make this a web page", "send this as a link", "host this", or wants to turn any markdown content into a URL. Also triggers on "publish a report", "share my notes", "create a page", or any request to make content accessible via a 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。
Set up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill whenever Python code will be executed for a SageMaker deployment, training job, or any AWS automation — including when about to run `pip install`, when about to invoke `boto3`, when creating or activating a virtualenv, or when the user asks to "set up the environment". Never use system Python and never `pip install` into it. Always isolate. This skill prevents the most common failure modes: wrong Python version, dependency conflicts, and stale SDKs.
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。
Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS account. Use it especially when the user has not specified a region or profile explicitly, when they say things like "use my AWS account", "deploy to AWS", "use my profile", or when about to make any AWS CLI or SDK call. Never guess the region or account ID — always use this skill to read it from the local configuration first.
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。
Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.
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。
Expert en DIY et making (3D printing, Arduino, woodworking, electronics, repair)
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。
Standardizes Makefile-based build and test workflows with reproducible targets. Use when creating or refining helpful build, test, and clean targets.
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。
Prepare a project for open sourcing: a sanitized fork with secrets and internal references stripped, a sanitizer verdict, README and LICENSE, then a new PRIVATE GitHub repo created and pushed only after GO. The playbook never makes the repo public. Use for "open source this project", "make a sanitized fork", "prepare a public release".
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 one reference image into a cleaned, scaled 3D asset: your own image-to-3D ComfyUI workflow makes the mesh, Blender decimates it to a poly budget, fixes scale, origin and material, and exports a .glb. Use for "image to 3D", "make a 3D model from this picture", "photo to glb".
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 a complete CI/CD pipeline for a project. Detects the stack, then generates and validates GitHub Actions workflows, a Dockerfile, and a Makefile as one coherent pipeline. Use when asked to "set up CI", "add pipeline", "create GitHub Actions", "ci/cd setup", "automate builds", "containerize", or "add a Makefile".
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 moments of joy, personality, and unexpected touches that make interfaces memorable and enjoyable to use. Elevates functional to delightful. Use when the user asks to add polish, personality, animations, micro-interactions, delight, or make an interface feel fun or memorable.
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。
Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management. Makes interfaces robust and production-ready. Use when the user asks to harden, make production-ready, handle edge cases, add error states, or fix overflow and i18n 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。