3.2万 件 ・ 関連度順
概要と使いどころ
End-to-end form handling with react-hook-form, Zod schemas, validation patterns, error messaging, field arrays, and multi-step wizards. Use for complex forms, validation architecture, autosave, field dependencies. Activate on "form validation", "react-hook-form", "Zod", "form error", "multi-step form", "wizard". NOT for simple HTML forms, backend validation only, or non-React frameworks.
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。
Audit whether a "current product focus receipt" (Decision/Now/Why-now/Evidence/Not-now/Cut-suspend/First-visible-proof/ Acceptance-gate/Kill-revisit-trigger/Owner/Review-date) and the work order it gates state a real, testable decision and a real agent launch — not planning-placeholder prose that sounds like an assignment but can't be proven. Use when deciding whether to launch an agent chain against a milestone or a stated "focus," when a work order lacks explicit input/output/owner/proof-gate, or when an acceptance gate would only prove a cached UI state instead of daemon truth. NOT for distinguishing roadmap items from energy-driven sidequests (legible-roadmap-with-sidequests), reviewing a PRD/prototype for product-completeness gaps like cold start or pricing (product-reality-reviewer), or accepting already-finished work against a personal acceptance bar (port-daddy-user-surrogate-pm-review).
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 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).
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 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。
Architects the encryption, codec/transport, and premium-feature layer of a group video-calling product, on top of an already-chosen SFU topology. Covers E2EE patterns (Zoom leader-fan-out, Signal pairwise-fan-out, MLS/TreeKEM as in Discord's DAVE, Telegram's ledger consensus), the SFrame (RFC 9605) + WebRTC Insertable Streams mechanism letting an SFU relay encrypted frames it can't read, codec/transport choice (AV1/VP9 SVC vs. simulcast, Opus, congestion control, Media-over-QUIC, WHIP/WHEP), and which "premium" features (virtual backgrounds, live captions, recording, breakout rooms, spatial audio) survive E2EE vs. structurally can't. Use when adding E2EE to an SFU-based call, choosing a 2026 codec/SVC strategy, or deciding which features to disable under E2EE mode. NOT for call topology/platform choice (see webrtc-adhoc-video-chat, which this composes with). NOT for one-way broadcast (see managed-video-streaming-pipeline). NOT for the DM/group-chat text backend (see realtime-messaging-backend-architecture).
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。
Decision-theoretic framework for agents embedded within the environments they model and act upon
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。
Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).
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。
Defensive counterpart to federated-harbor-redteam: closes the smells that red team opens against The Federated Harbor whitepaper. Federation-specific defenses for cross-harbor primitives — mechanization commitments, scope hedges, cross-paper dependency formalization, pre-emptive analogies (CT, Macaroons, atomic swaps), and defense-in-depth framing (refuses vs prices). Use during a versioned red-vs-white round; pairs with federated-harbor-redteam. NOT for ad-hoc code review, NOT for the Anchor or Bonded papers (use whitehat-defense).
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。
Build face recognition systems with InsightFace, ArcFace, enrollment pipelines, HDBSCAN clustering, and privacy-compliant architecture. Activate on: face recognition, face enrollment, face clustering, identity verification, facial search. NOT for: general object detection (computer-vision-pipeline), emotion analysis (ai-engineer).
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。
Foundational impossibility result proving consensus cannot be guaranteed in asynchronous systems with even one faulty process
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。
Adversarial reviewer for The Federated Harbor whitepaper — the third paper in the Curiositech sequence after Anchor and Bonded Commons. Probes federation-specific threats: trust transitivity, cross-harbor token forgery, federated revocation under partition, cross-harbor Sybil, cross-domain settlement, equivocation, bond-pool draining, cold-start joining, federation-operator Sybil. Use during a versioned red-vs-white round; pairs with federated-harbor-whitehat. NOT for incident response, NOT for the Anchor or Bonded papers (use redteam-review).
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。
Build low-fidelity wireframes, screen mockups, and user-flow diagrams in Frame0 (the hand-drawn Balsamiq-style wireframing tool) through its connected MCP server. Use when asked to wireframe a screen, sketch a UI, make a low-fi mockup, lay out an app's screens, or diagram a user flow with clickable links. Triggers: "wireframe", "frame0", "low-fi mockup", "sketch a screen", "user flow", "lo-fi", "rough out the UI". NOT for high-fidelity visual design, brand systems, or color/typography polish (use web-design-expert / Figma); NOT for production UI code (use frontend 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。
Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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。
Design resilient React error handling with Error Boundaries, Sentry integration, recovery UI, retry patterns, and graceful degradation. Activate on: error boundary, crash recovery, Sentry, error fallback UI, retry logic, unhandled exceptions. NOT for: form validation errors (use form-validation-architect), API error codes (use api-architect).
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。
Message queues, pub/sub, event sourcing with Kafka, RabbitMQ, Redis Streams. Activate on: event-driven, message queue, pub/sub, Kafka, RabbitMQ, event bus, async messaging, dead letter queue. NOT for: CQRS projections (use cqrs-event-sourcing-architect), real-time WebSocket (use websocket-realtime-expert), observability (use observability-apm-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。
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。
Classify every destructive/gated action an agent body can attempt (git, filesystem, network, shell, github) into block/approve/allow tiers, and audit whether the pre-tool and post-tool governance backing that classification is real: blocked actions proven zero-side-effect by a negative fixture, every denial backed by a receipt and a transcript event, every block-tier denial paired with a safe alternative, and no unmanaged or same-UID body ever marked "contained." Use when building or reviewing Agent Harbor's C5 governance gate (destructive git blocker, approval request/result, denial receipts), gating a new tool surface before it can run destructive commands, or auditing whether an existing "destructive-action blocked" claim actually has evidence behind it. NOT for proving an existing sandbox boundary actually contains an adversary once an action is isolated (use sandboxed-adversarial-test-harness), deciding where in a DAG to place a human review node or designing the approval UX itself (use human-gate-designer), or designing the general work-receipt schema across an entire agent task (use agent-work-receipt-designer).
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。
Manage database schema with Drizzle ORM and SQLite migrations. Use when adding tables, modifying columns, creating indexes, or running migrations. Activates for database schema changes, migration generation, and Drizzle query 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。
Design desktop window systems that feel native on macOS and Windows: split views, inspectors, auxiliary windows, tiling, snap-safe sizes, default placement, and chrome density. Use when a Tauri/Electron/WinUI/SwiftUI app feels awkward, overlapping, over-chromed, or generic, or when you need a real geometry contract for multiple surfaces. NOT for mobile layouts, marketing pages, or CSS-only component styling without multi-window or multi-pane behavior.
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。
Decompose DAGs into execution chains using width bounds, stratification, virtual nodes, and matching. Use when minimizing workflow lanes in dependency graphs. NOT for cyclic graphs, generic scheduling, or one-off queries with no preprocessing payoff.
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 production-ready design tokens from natural language descriptions. Outputs Tailwind configs, CSS custom properties, and DTCG W3C tokens from 24 trends + 31 AI-ready styles with 2800+ component examples.
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。
Builds comprehensive design systems and design bibles with production-ready CSS. Expert in design tokens, component libraries, CSS architecture. Use for design system creation, token architecture, component documentation, style guide generation. Activate on "design system", "design tokens", "CSS architecture", "component library", "style guide", "design bible". NOT for typography deep-dives (use typography-expert), color theory mathematics (use color-theory-palette-harmony-expert), brand identity strategy (use web-design-expert), or actual UI implementation (use web-design-expert or native-app-designer).
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。