1,338 件 ・ 関連度順
概要と使いどころ
Extract structured data from IFC (Industry Foundation Classes) files using IfcOpenShell. Parse BIM models, extract quantities, properties, spatial relationships, and export to various formats.
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 parent/child agent relationships with task delegation and result aggregation. Supports sequential chains, parallel fans, conditional routing, retry logic, timeout handling, and YAML-based visual workflow definition.
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。
Efficiently route multi-stop trips with time management. Include transportation, restaurant/activity reservations timeline, and buffer time for spontaneity.
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。
Point Cowork at your invoices and payments records -- builds an AR aging report, drafts escalating follow-up emails matched to each invoice's age and the client relationship, and runs as a weekly scheduled task so nothing slips past 30 days unnoticed.
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。
Designs relational and document database schemas from requirements or an existing app - tables and collections, keys, relationships, constraints, indexes driven by real query patterns, ERDs, and reversible migration scripts - with PostgreSQL (including Supabase) as the default and MySQL, SQLite, and MongoDB supported. Use when the user wants to model data for a new app or feature, review or fix an existing schema, choose keys or indexes, plan multi-tenancy, normalize or denormalize, or write CREATE TABLE statements or migrations, even if they just describe their app and ask "how should I store this". For moving data between database providers, use database-migrator.
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 to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.
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。
SwiftData patterns — autosave, relationships, dangerous predicates, CloudKit constraints, indexing, class inheritance. Use when writing, reviewing, or debugging SwiftData code.
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。
Generates a Mermaid dependency graph showing import relationships between modules. Use when analyzing coupling, finding circular deps, or planning refactors.
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。
Generates a Mermaid architecture diagram showing high-level component relationships. Use when visualizing how plugins or modules fit together.
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。
Sweep plugins, skills, agents, commands, and hooks after a model release or Claude Code version bump. Use when upstream ships. Do not use for routine edits; use night-market-change-control.
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。
Personal CRM and contact management - manage contacts, relationships, and interactions. Use when the user discusses contacts, people, or relationship tracking.
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。
Honey for plain Claude — the terse-prose core with no agent-harness features. Paste into a claude.ai Project's custom instructions, a Style, or an API system prompt. Strips filler, hedging, and pleasantries from every response while keeping facts, names, numbers, steps, and code exact. No tools 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。
Turn long videos & livestream VODs into viral vertical shorts, 100% locally — on-device transcription, LLM highlight detection, 9:16 reframe with karaoke captions, and a per-clip render-QA report. Use when the user asks to clip / cut / 切片 / 剪 a long video, podcast or stream replay into short clips, find highlights / 爆点 in a video, or transcribe a media file. Footage never leaves the machine.
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 polishing, diagnosing, tailoring, or exporting resumes for LLM, RAG, Agent, Agentic RL, post-training, pretraining, AIGC, search/ranking, multimodal, AI backend, or LLM algorithm internships from raw resume text, a materials folder, and/or a target job description. Audits evidence, maps JD fit, enforces truth boundaries, writes polished and targeted resumes, generates interviewer-style grilling questions, answer cards, evidence-upgrade plans, and optional open-source project recommendations without fabricating experience.
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。
Analyses the limitations on consent as a lawful basis for processing employee data under Art. 88 GDPR and WP29 Opinion 2/2017. Addresses power imbalance in employment relationships, identifies alternative lawful bases, and maps national derogations. Keywords: consent, employment, power imbalance, Art. 88, WP29, lawful basis, employee data, labour law.
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。
Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management. Applies Art. 9(2)(b) employment obligations and Art. 9(2)(h) health professional exceptions. Covers data minimisation, occupational health provider relationships, and return-to-work procedures. Keywords: health data, Art. 9, occupational health, fitness-for-work, special category, employment, sickness absence.
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。
Determines controller-processor relationships for AI services and conducts privacy due diligence. Covers SaaS AI (processor), embedded AI (joint controller), API-based AI (assessment framework), and vendor risk assessment. Keywords: AI vendor, controller-processor, due diligence, SaaS AI, joint controller, Art. 28.
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 generating or refactoring Spring Boot 4 JPA entities, repositories, queries, projections, persistence tests, entity relationships, embeddables, IDs, or Hibernate mappings. Covers Jakarta Persistence 3.2 imports, Hibernate 7 entity modeling, new-state detection, N+1 prevention, projections, keyset pagination, batch writes, and common agent mistakes.
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。
Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.
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 an iOS App Clip target to an Expo app. Use when the user mentions App Clip, AASA, apple-app-site-association, appclips, smart app banner, or wants to ship a lightweight iOS Clip invoked from a URL alongside their parent app.
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。
Narrative-driven animation skill for explanatory content and visual storytelling. **Triggers when:** - User wants to explain a concept or process - Request involves step-by-step demonstrations - Content is educational or tutorial-like - User mentions "explain", "show how", "demonstrate", "walk through" **Capabilities:** - Breaking concepts into digestible visual steps - Progressive revelation of information - Highlighting cause-and-effect relationships - Building intuition through visual metaphors
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。
Mathematical visualization skill for equations, proofs, and geometric concepts. **Triggers when:** - User mentions equations, formulas, or mathematical expressions - Request involves mathematical proofs or derivations - Content includes geometric relationships - User mentions LaTeX, calculus, algebra, geometry, trigonometry - Patterns: "equation", "formula", "prove", "derive", "graph", "plot" **Capabilities:** - LaTeX equation rendering with color-coded components - Function graphing and transformations - Geometric constructions and proofs - 3D mathematical surfaces - Step-by-step derivations with highlights
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 "create a character", "update a character", "add a character", "build a family tree", "character relationships", "character timeline", "character arc", "character profile", "relationship graph", "name a character", or needs to manage characters in a story project. NOT for recording or checking character voices (use voice-style), rewriting dialogue so the voices differ (use line-editing), or a thematic arc's lie, truth, and arc type (use theme-craft).
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 about "theme", "controlling idea", "thematic argument", "moral argument", "thematic arc", "flat arc", "negative arc", "the lie", "antagonist design", "motif", "symbolism", "theme audit", or wants to plan, track, or revise the thematic layer of a story, including the lie, truth, ghost-wound, and arc-type fields of a character file. NOT for finding or testing a story premise (use premise-workshop), or a character's profile, relationships, or "character arc" record (use character-management).
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。