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概要と使いどころ
Draft a detailed privacy policy covering data types, jurisdiction, GDPR and compliance considerations, and clauses needing legal review. Use when creating a privacy policy, updating data protection documentation, or preparing for compliance.
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 refined user personas from research data — 3 personas with JTBD, pains, gains, and unexpected insights. Use when building personas from survey data, creating user profiles from research, or segmenting users for product decisions.
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 realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script). Use when creating test data, building mock datasets, or generating sample data for development and demos.
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。
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction patterns.
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。
Segment users from feedback data based on behavior, JTBD, and needs. Identifies at least 3 distinct user segments. Use when segmenting a user base, analyzing diverse user feedback, or building a segmentation model.
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。
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.
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 SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring databases, or translating business questions into queries.
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。
Identify the Ideal Customer Profile (ICP) from research data with demographics, behaviors, JTBD, and needs. Use when defining your ICP, analyzing PMF survey data, or understanding who your best customers are.
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 images and text via reverse-engineered Gemini Web API. Supports text generation, image generation from prompts, reference images for vision input, and multi-turn conversations. Use when other skills need image generation backend, or when user requests "generate image with Gemini", "Gemini text generation", or needs vision-capable AI generation.
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, dark-themed SVG diagrams of any type — architecture diagrams, flowcharts, sequence diagrams, structural diagrams, mind maps, timelines, illustrative/conceptual diagrams, and more. Use this skill whenever the user asks for any kind of technical or conceptual diagram, visualization of a system, process flow, data flow, component relationship, network topology, decision tree, org chart, state machine, or any visual representation of structure/logic/process. Also trigger when the user says "画个图" "画一个架构图" "diagram" "flowchart" "sequence diagram" "draw me a ..." or uploads content and asks to visualize it. Output is always a standalone .svg file.
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。
Orchestrate the live-ops team — live-ops-designer, economy-designer, analytics-engineer, community-manager, writer — for a season or live event.
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。
Auto-generate a changelog from git commits and sprint data. Internal and player-facing versions.
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。
Break one epic into implementable stories embedding TR-ID, ADR guidance, acceptance criteria. Reads the control manifest. After /create-epics.
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。
Configure engine and version. Pins it in CLAUDE.md; WebSearch fills reference docs when the version is beyond LLM training data.
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。
Per-asset visual specs plus AI generation prompts from GDDs and character profiles. After the art bible.
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 balance outliers, broken progressions, degenerate strategies, economy imbalances in formulas and data. 'Check game balance'.
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。
Execute a plan or concrete work prompt end-to-end. Use when implementing from a plan document, a spec path, or a clear build request; use ce-debug for open-ended bugs. Use when an outer orchestrator needs implementation and local verification only, without the shipping tail.
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。
Analyze and design control flows and data structures. Produces compact ASCII tree diagrams showing triggers, call chains, payload shapes, state mutations, and re-render effects. Use when user asks to diagram, trace, visualize, or design a flow or data structure.
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。
Drive the running OpenWork app over CDP from the shell, headless by default (nothing opens on screen). Evaluate JS, take screenshots, open a new session, send a prompt with a chosen model, wait for the run to finish. Use when checking a UI change by hand in a world or pnpm dev, or when reproducing a chat state.
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 multi-vendor AI provenance marks: invisible Unicode (Layer A), statistical text watermarks via rewrite (Layer B, always offer), and C2PA/EXIF/XMP/container metadata on PNG/JPEG/WebP/SVG/PDF/DOCX/ODT/HTML/MD/TEX. Covers Claude, Gemini/SynthID-class, OpenAI provenance, and open-LLM sampling marks. Use when the user asks to strip watermarks, remove C2PA/Content Credentials, clean AI metadata, remove invisible Unicode, anti-detect clean AI output, or runs /remove-ai-marks (aliases: /remove-claude-marks).
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 OpenSEO in the current AI agent. Use when a user pastes the OpenSEO installation prompt or asks to connect its plugin, MCP, and 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。
Find the questions people ask about a market, how ChatGPT answers them, and which sites get cited in the answers. Use when the user asks what people ask AI about their niche, wants prompt ideas, or wants to know where their brand is missing before choosing prompts to track. Research only; it never saves tracking or starts answer collection.
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。
Validate n8n expression syntax and fix common errors. Use when writing n8n expressions, using {{}} syntax, accessing $json/$node variables, troubleshooting expression errors, mapping data between nodes, or referencing webhook data in workflows. Use this skill whenever configuring node fields that reference data from previous nodes — expressions are how n8n passes data between nodes, and getting the syntax wrong is the most common source of workflow errors. Also use when asked whether a complex expression hurts performance.
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。
Handle files and binary data in n8n correctly. Use when working with files, images, PDFs, attachments, uploads or downloads, base64, vision/multimodal input, or when an AI agent needs a file as tool input or output — and whenever the user mentions $binary, binaryPropertyName, "read the PDF", "attach the file", "send the image", Merge losing binary, or a CDN for chat images. Covers the $binary vs $json split, reading/writing binary, keeping binary alive across transforms with Merge, the agent-tool binary boundary, and the CDN/URL requirement for chat surfaces.
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。