「graph」の検索結果

AI design language for production-grade UI — 10 commands covering typography, color, motion, layout, and UX writing quality

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.

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 visual territories (mood boards) for team alignment before production. Groups references into 2-4 named territories, each with palette, texture, typography feel, and 4-6 generated sample tiles, so a team can agree on a direction. Use when the user says "moodboard", "visual territories", "align the team on a look", "reference board", or needs stakeholder sign-off on aesthetic before generating final assets. Part of the Creative Production set.

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 product-in-use lifestyle scenes. Places the product in believable contexts of use (who, where, when, doing what) with natural lighting and real texture, for lifestyle/editorial/ecommerce. Use when the user says "lifestyle shot", "product in use", "scene", "show it being used", "in-context photography", or needs people/environment around the product. Part of the Creative Production set.

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。

Semantic search, grep, and Q&A across codebases and documentation indexed in CodeAlive. Use when the user mentions "CodeAlive", asks to list or get data sources, list indexed repositories, search code or docs across remote repos, fetch artifact content, or trace call graphs across repositories.

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。

Italian geographic and property data through Openapi - geocoding/reverse geocoding, zip codes (CAP), municipalities/provinces/regions with ISTAT codes, Italian cadastre (catasto) property and owner lookups, visure catastali/ipotecarie, real estate valuations.

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。

Designs the first screen visitors see — the hero section. Layout patterns (split, centered, asymmetric, full-bleed), navbar design, headline typography, CTAs, background treatments (gradients, video, particles, 3D), scroll cues, and above-the-fold conversion strategy. Activate on 'hero section', 'landing page hero', 'above the fold', 'first impression', 'homepage header', 'navbar design', 'hero layout', 'landing page design'. NOT for full multi-page site architecture (use web-design-expert), not for SEO content strategy (use seo-visibility-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。

Makes iOS apps feel premium, polished, and unmistakably native — SF Symbols mastery, SwiftUI spring animations, haptic feedback choreography, blur/vibrancy materials, Dynamic Type, color system design, and the specific spacings and radii Apple uses. This is about TASTE, not syntax. Activate on 'iOS design polish', 'SwiftUI animation', 'SF Symbols', 'haptic feedback', 'premium iOS feel', 'Apple HIG', 'native iOS look', 'Liquid Glass', 'iOS visual design', 'app polish'.

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。

Professional network graph analyst identifying Gladwellian superconnectors, mavens, and influence brokers using betweenness centrality, structural holes theory, and multi-source network reconstruction. Activate on 'superconnectors', 'network analysis', 'who knows who', 'professional network', 'influence mapping', 'betweenness centrality'. NOT for surveillance, discrimination, stalking, privacy violation, or speculation without 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。

Use when building APIs on Hono (Cloudflare Workers, Bun, Deno, Node), debugging route ordering, wiring middleware, validating with @hono/zod-validator, returning streaming responses, configuring CORS with credentials, handling errors via app.onError, or composing typed RPC clients. Triggers: c.env binding types, c.header + c.redirect interaction, missing await next() bugs, Set-Cookie not attaching to redirect, route-precedence surprises, JWT middleware setup, hono/client typed RPC end-to-end. NOT for Express/Fastify/Koa idioms, tRPC/GraphQL paradigms, or Next.js Route Handlers.

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。

Wave-based parallel scheduling for DAG execution. Manages execution order, resource allocation, and parallelism constraints. Activate on 'schedule dag', 'execution waves', 'parallel scheduling', 'task queue', 'resource allocation'. NOT for building DAGs (use dag-graph-builder) or actual execution (use dag-parallel-executor).

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 modern, intuitive DAG/workflow visual editors that feel like LEGO, not LabView

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 design trends and recommend appropriate styles, color palettes, and typography systems for your project based on current design movements. NOT for accessibility auditing or full design system creation.

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。

Long-running design anthropologist that builds comprehensive visual databases from 500-1000 real-world examples, extracting color palettes, typography patterns, layout systems, and interaction design across any domain (portfolios, e-commerce, SaaS, adult content, technical showcases). This skill should be used when users need exhaustive design research, pattern recognition across large example sets, or systematic visual analysis for competitive positioning.

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。

Master of text-based visual communication using ASCII art, Unicode box-drawing, and structured diagram notation. Creates clear, maintainable diagrams for systems, processes, hierarchies, relationships, and psychological structures. Proactively generates diagrams to enhance understanding. Activate on visualization needs, system architecture, process flows, psychological mapping, or when complex concepts would benefit from visual representation. NOT for photo editing, vector graphics, or GUI-based design tools.

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。

Validates DAG structures, performs topological sorting, detects cycles, and resolves dependency conflicts. Uses Kahn's algorithm for optimal execution ordering. Activate on 'resolve dependencies', 'topological sort', 'cycle detection', 'dependency order', 'validate dag'. NOT for building DAGs (use dag-graph-builder) or scheduling execution (use dag-task-scheduler).

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。

Time-travel debugging for DAG executions. Inspect agent state at any node, replay decisions with modified inputs, compare execution traces side-by-side, and identify where reasoning diverged. Inspired by LangGraph Studio's state-editing model and Temporal's event history. Activate on "debug DAG", "replay execution", "time travel debug", "inspect node state", "what went wrong at step", "compare runs", "execution diff". NOT for live monitoring (use dag-runtime + websocket-streaming), failure analysis (use dag-ops), or general code debugging.

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。

Executes DAG waves with controlled parallelism using the Task tool. Manages concurrent agent spawning, resource limits, and execution coordination. Activate on 'execute dag', 'parallel execution', 'concurrent tasks', 'run workflow', 'spawn agents'. NOT for scheduling (use dag-task-scheduler) or building DAGs (use dag-graph-builder).

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, validates, schedules, and dynamically modifies DAG execution graphs. Decomposes problems into nodes with dependencies, performs topological sorting, detects cycles, resolves conflicts, and schedules wave-based parallel execution. Use when designing a DAG structure, validating dependencies, planning execution order, or modifying a DAG at runtime. Activate on "build DAG", "plan workflow", "DAG dependencies", "topological sort", "schedule execution", "modify DAG", "replan". NOT for executing DAGs (use dag-runtime), validating outputs (use dag-quality), or matching skills to nodes (use dag-skills-matcher).

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。

Modifies DAG structure during execution in response to failures, new requirements, or runtime discoveries. Supports node insertion, removal, and dependency rewiring. Activate on 'replan dag', 'modify workflow', 'add node', 'remove node', 'dynamic modification'. NOT for initial DAG building (use dag-graph-builder) or scheduling (use dag-task-scheduler).

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。

Algorithms for decomposing DAGs into chains for parallel execution and resource optimization

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。

Strategic analyst that maps competitive landscapes, identifies white space opportunities, and provides positioning recommendations. Use when users need competitive analysis, market positioning strategy, differentiation tactics, or "how do I stand out?" guidance across any domain (portfolios, products, services). NOT for market size estimation or financial forecasting.

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。

Conversation patterns and interaction protocols for multi-agent systems. Covers request/response, pub/sub, blackboard, delegation chains, debate, critique, consensus, fan-out/fan-in, supervisor-worker, and peer negotiation. Deep analysis of AutoGen conversation patterns, CrewAI delegation, LangGraph state passing, and FIPA-ACL performatives. Teaches how to design what agents say to each other and in what order. Activate on: "agent conversation", "agent protocol", "multi-agent debate", "agent delegation", "supervisor worker pattern", "agent voting", "consensus protocol", "fan-out fan-in", "agent negotiation", "blackboard pattern", "agent dialogue", "conversation topology", "agent handoff". NOT for: wire format or serialization (use agent-interchange-formats), orchestration infrastructure (use agentic-infrastructure-2026), single agent behavior (use agentic-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。

Build and adopt production AI agent infrastructure in 2026. Covers framework selection (LangGraph, CrewAI, AutoGen, MCP), orchestration patterns, evaluation, observability, memory systems, and tool use. Also covers the SOCIAL dimension: how to sell agent infrastructure internally, change management, measuring ROI, building trust in autonomous systems, and scaling adoption across teams. Activate on: "agent infrastructure", "agent framework comparison", "which agent framework", "sell AI tools internally", "agent adoption", "agent observability", "agent evaluation", "MCP architecture", "agentic mesh", "enterprise AI agents", "AI change management", "agent ROI". NOT for: building specific agents (use ai-engineer), designing agent behavior patterns (use agentic-patterns), prompt tuning (use prompt-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。