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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, game-design intake see game-design-shaper.

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

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。

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

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。

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

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。

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

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。

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

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。

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

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。

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

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.

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。

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

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。

Train an ML model in the QuantConnect ML-Training-Pipeline with thermal-safe GPU usage and rigorous validation. Arguments: <architecture|script> [--dry-run] [--seeds 0,1,7,42,99] [--folds 5] [--bg]

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。

Persistent, adaptive vector memory for agents on a ruOS desktop — a Rust-native vector database with local semantic embeddings, HNSW retrieval, and graph relationships. Use to remember and recall across sessions with no database server or API key.

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Store and semantically search agent memory with ONNX vector embeddings on a ruOS desktop, using the Ruflo CLI. Use to persist patterns/decisions across sessions and recall them by meaning rather than exact key.

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。

Publication-quality statistical visualization with mandatory best practices. Use when creating plots, charts, figures, or any data visualization. Enforces accessibility, uncertainty display, proper labeling, and statistical accuracy.

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Summary statistics, data exploration, and descriptive analysis. Use for: summary stats, describe data, data exploration, distributions, means, medians, correlations, cross-tabs.

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Analyze data from randomized controlled trials. Use when user mentions: treatment effects, ITT analysis, LATE, TOT, compliance analysis, attrition, balance checks, heterogeneous effects, RCT results, experimental analysis.

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。