데이터·AI 스킬

Structures a vague engineering request into a well-scoped task brief before any implementation begins. Use when the user has an engineering goal but the ask is missing which repos are in scope, what "done" means, constraints, or open questions. Triggers on "shape this", "scope this out", "frame this work", "write a brief for", "I want to build" (with unclear scope), or the /shape slash command. Produces a filled task template (multi-repo feature, single-repo change, investigation, or bugfix). Not for already-scoped work — go straight to execution. If the domain is unclear, ask one qualifying question before routing — for marketing intake see marketing-shaper (marketing pack: `--with-marketing`), game-design intake see game-design-shaper (games pack: `--with-games`).

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Use when implementing analytics with PostHog in a TypeScript app — capturing events, identifying users, adding feature flags, tracking errors, or wiring API lifecycle telemetry. Triggers on edits to analytics integration files, or mentions of "PostHog", "analytics", "feature flag", "event tracking", "capture", "identify", "A/B test", or "experiment".

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Catalog APIs, persistence models, and message/event payloads into DATA_MODEL.md at the project root. Use after implementation when a diff touches request/response types, schemas, ORM models, queue payloads, or webhook shapes. Triggers on "document data model", "update DATA_MODEL", "catalog API shapes".

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Use when building data pipelines, ETL jobs, event processors, message-broker producers/consumers, application caching layers, database migrations, BigQuery queries, or event-sourcing handlers in TypeScript. Triggers on edits to indexer/ETL/migration code, Prisma or Drizzle schemas, BigQuery integration code, RabbitMQ/Kafka/SQS/BullMQ producer or consumer code, Redis cache wrappers, or mentions of "data engineering", "ETL", "pipeline", "indexer", "event sourcing", "data warehouse", "data migration", "message queue", "RabbitMQ", "Kafka", "SQS", "BullMQ", "Redis cache", or "caching".

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Adversarially verifies DATA_MODEL.md property rows against cited Source files. Use after data-model-documenter when DATA_MODEL.md changed — inventories each property in added/changed catalog sections and classifies VERIFIED / REFUTED / UNVERIFIABLE. Triggers on "verify DATA_MODEL", "check catalog against source", "data model verification".

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End-of-session pass that persists durable facts from the CURRENT session into .claude/memory/. Runs IN-SESSION in the main agent (never via Task — a subagent starts cold with no transcript), prompted by the Stop hook's nudge. Triggers on "persist durable facts from this session", "run memory-extraction", "flush session memory", or "extract memory before close". Reads the in-context transcript plus existing memory, applies the durable-fact predicate below, and writes one file per fact plus one MEMORY.md index line — append-or-update, never clobbering a consumer's existing memory.

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Search and analyze X (Twitter) using xAI Grok 4 via OpenRouter with Live Search. Trigger on prompts that explicitly or implicitly ask to "search Twitter/X", "what's trending", "tweets from @handle", "hashtag #…", "what are people saying", or that require tweet-level activity/engagement from X.

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Optimizes natural-language image requests and rough prompts into ready-to-use GPT Image 2.5 prompts using the official prompting guide as a live reference. Use when users ask to improve image prompts, 优化生图提示词, 把想法变成提示词, or write prompts for GPT Image 2.5 Flare or Sunburst. Produces prompt text, not images, unless the user explicitly asks to generate.

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Next.js AppRouter における、データフェッチング、データベースへのクエリ発行のベストプラクティス。データフェッチを伴う処理を実装、変更する場合はこのドキュメントを参照すること。

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Generate database migration, model update, and seed data

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Eng manager-mode plan review. Lock in the execution plan, data flow, diagrams, edge cases.

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Design or change dygo Entity metadata, Fields, Record Collections, links, naming, routes, indexes, and constraints. Use when a business data model or metadata contract is the main task.

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Create or review dygo Fixtures and explicit Patches for reference data, setup Records, backfills, renames, and unsafe lifecycle transitions. Use when metadata sync alone cannot express the required data change.

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Automate Asin Data API tasks via Rube MCP (Composio). Always search tools first for current schemas.

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Automate AI ML API tasks via Rube MCP (Composio). Always search tools first for current schemas.

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Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Use when planning features that need thorough pre-implementation analysis.

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Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory

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Smart dependency management for any language. Auto-detects project type, applies safe updates automatically, prompts for major versions, diagnoses and fixes dependency issues.

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Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot

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Analyze cryptographic code to detect operations that leak secret data through execution timing variations.

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Elite content marketing strategist specializing in AI-powered content creation, omnichannel distribution, SEO optimization, and data-driven performance marketing.

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Implement routing in Angular v20+ applications with lazy loading, functional guards, resolvers, and route parameters. Use for navigation setup, protected routes, route-based data loading, and nested routing. Triggers on route configuration, adding authentication guards, implementing lazy loading, or reading route parameters with signals.

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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

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AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

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