データ・AIのスキル

Analyze any codebase's source code in depth and produce structured analysis documents saved as markdown files. Use this skill whenever the user asks to understand how a codebase works — architecture, module design, call flows, data models, design patterns, performance characteristics, or any implementation detail. Trigger on phrases like "analyze the source", "explain this code", "how does X work", "where is Y implemented", "trace the flow of", "what happens when", "read through the code", "code walkthrough", "源码分析", "代码解读", "实现原理", "架构分析", "调用链路", "模块分析", or any code-exploration request. Works with any programming language: TypeScript/JavaScript, Java, Python, Go, Rust, C/C++, and more. Even if the user's question seems simple (e.g., "这个文件是干什么的"), use this skill — a thorough, source-backed analysis document is always more valuable than a surface-level guess.

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。

Understand and customize the local Trellis architecture inside a user project. Use when modifying .trellis plus platform hooks, settings, agents, skills, commands, prompts, or workflows generated by trellis init.

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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Generate a realistic-human, dialogue-driven short-drama clip — one shot, or a few hard-cut shots inside one job — from a script or scene description using the Ofox video API (Seedance 2.5). Runs a short creative brief when the input leaves beat, aspect ratio, emotional arc or camera register open (one held take, a travelling take, or a multi-shot cut list) ("Let the AI decide" is offered on the taste questions, never on a must-ask one, and never as the default), writes a structured prompt (header manifest, timestamped shots, quoted dialogue with delivery notes, consistency lock), shows a cost estimate, then calls ofox-video-core to submit, poll, download, and report the real cost. Use when a user asks to turn a script beat into video, e.g. "generate scene 3 of this script, two characters talking, 15 seconds", "make a vertical short-drama clip of these two arguing in a kitchen", "turn this dialogue into a 12-second video", or "give me a realistic short-drama shot of a couple breaking up at a train station". Do not use for silent product/brand shots (see seedance-ad-creative), for anime- or manga-styled scenes (see seedance-anime-drama), for one person addressing the viewer rather than another character — a script read from a supplied portrait is talking-head, an idea pulled out of an article is explainer — or for anything not involving people/dialogue.

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。

Requires OFOX_API_KEY — create one at https://app.ofox.ai. Generate cheap vertical 9:16 drafts in one priced batch, pick a winner off the contact sheet, then re-render only that one. The cheap tier is the point — several times cheaper per second, so a whole set can cost less than one flagship clip. Use when a user wants Shorts/Reels/TikTok raw material rather than one finished video, e.g. "give me 5 vertical clips to choose from", "a few Reels drafts for this product", "some cheap options before we commit", or "batch me some 9:16 takes". Do not use when one finished clip is wanted — go straight to the scenario skill (seedance-ad-creative, ugc-ads, seedance-short-drama, seedance-product-video), which is also where this skill gets the prompt it drafts.

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。

Enriches inbound leads with firmographic and technographic data. Takes minimal lead info and enriches via WebSearch, Apollo, or ZoomInfo to produce a complete lead record with company size, revenue, tech stack, social profiles, and decision-maker details.

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Builds Quarterly Business Review decks for active clients. Pulls metrics, generates structured QBR with wins, challenges, roadmap, and recommendations. Uses crm-writer to read client 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。

Revenue forecast from pipeline data with stage-weighted probability and sensitivity analysis

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Generates full long-form content: whitepapers, eBooks, research reports, and pillar pages. Takes a content brief and produces 2000-5000 word drafts with sections, data points, and CTAs.

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 validated JSON-LD structured data markup for any page type

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。

Apply rapport-based elicitation to resistant or semi-cooperative humans and agents. Use when coercive prompting or brittle handoffs damage cooperation. NOT for routine cooperative tasks, pure technical debugging, or already reliable exchanges.

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Apply rapport-based elicitation to resistant or semi-cooperative humans and agents. Use when coercive prompting or brittle handoffs damage cooperation. NOT for routine cooperative tasks, pure technical debugging, or already reliable exchanges.

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。

S3, multipart uploads, CDN integration, and presigned URLs for file storage. Activate on: file upload, S3, presigned URL, multipart upload, CDN, blob storage, image upload, media storage. NOT for: data warehouse storage (use lakehouse-architect), database design (use dimensional-modeler).

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 high-quality datasets for LLM fine-tuning with filtering, deduplication, augmentation, and RLHF data formatting. Activate on: fine-tuning data, training data curation, RLHF dataset, data quality filtering, SFT dataset. NOT for: model training infrastructure (ai-engineer), prompt engineering without fine-tuning (prompt-engineer).

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Use when running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).

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Design dashboards for migrations and runtimes. Use for authority drift, verifier status, burn-down, runtime health, or pain panels. NOT for vanity analytics, ad hoc charts, or duplicate reporting.

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Use for sensemaking, frame revision, anomaly handling, questioning strategy, and ambiguity diagnosis with the Data/Frame model before action is chosen. NOT for deterministic classification, settled execution planning, or situations where the frame is already stable.

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。

Flutter state management expert with BLoC/Cubit, Riverpod, Provider, and Navigation 2.0 (GoRouter). Activate on: Flutter state management, BLoC pattern, Cubit, Riverpod, Provider, GetX, GoRouter, Flutter navigation, flutter_bloc. NOT for: React Native (use react-native-architect), SwiftUI (use swiftui-data-flow-expert), Jetpack Compose (use jetpack-compose-navigation-expert).

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 in drone systems, computer vision, and autonomous navigation. Specializes in flight control, SLAM, object detection, sensor fusion, and path planning. Activate on "drone", "UAV", "SLAM", "visual odometry", "PID control", "MAVLink", "Pixhawk", "path planning", "A*", "RRT", "EKF", "sensor fusion", "optical flow", "ByteTrack". NOT for domain-specific inspection tasks like fire detection, roof damage assessment, or thermal analysis (use drone-inspection-specialist), GPU shader optimization (use metal-shader-expert), or general image classification without drone context (use clip-aware-embeddings).

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。

dbt Core/Cloud data transformations, testing, documentation, and CI/CD. Activate on: dbt, data transformation, analytics engineering, ref, source, staging model, mart, dbt test. NOT for: orchestration/scheduling (use airflow-dag-orchestrator), data warehouse tuning (use data-warehouse-optimizer).

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。

### 1. The Fault/Error/Failure Hierarchy NOT for unrelated tasks outside this domain.

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。

Star schema, snowflake schema, SCD types, and Kimball methodology for analytical data modeling. Activate on: dimensional model, star schema, snowflake schema, SCD, fact table, dimension table, Kimball, grain, surrogate key. NOT for: dbt implementation (use dbt-analytics-engineer), warehouse tuning (use data-warehouse-optimizer).

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。

Large-scale data migrations with validation, rollback, and zero-downtime strategies. Activate on: data migration, database migration, zero-downtime migration, dual-write, backfill, cutover, data validation, schema migration. NOT for: schema evolution in streams (use schema-evolution-manager), API versioning (use api-versioning-backward-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。

Great Expectations, dbt tests, anomaly detection, and data contracts for data quality. Activate on: data quality, data validation, Great Expectations, data contract, anomaly detection, SLA, freshness check, schema validation. NOT for: dbt model structure (use dbt-analytics-engineer), schema evolution (use schema-evolution-manager).

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。

State-of-the-art data visualization for React/Next.js/TypeScript with Tailwind CSS. Creates compelling, tested, and accessible visualizations following Tufte principles and NYT Graphics standards. Activate on "data viz", "chart", "graph", "visualization", "dashboard", "plot", "Recharts", "Nivo", "D3". NOT for static images, print graphics, or basic HTML tables.

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。