Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
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。
26 件 ・ 関連度順
概要と使いどころ
Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
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。
Deep file-focused code review for correctness bugs. Unlike shallow-review which runs 6 specialists in parallel across the entire patch, deep-review focuses on user-specified files with full pattern catalogs (500+ patterns), codebase investigation, and source-level context gathering. Use when: the user specifies particular files for focused review, a shallow review flagged areas that need deeper investigation, reviewing critical-path code changes, examining complex serialization/lifecycle/state-machine changes. The user instructs which files to focus on (typically a subset of files in the patch).
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。
Renders every state of a component you choose on a throwaway page, with mock data and a switcher, so you can work on each state.
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。
Model component behaviour as explicit states, events, and transitions. Use when a component has many interacting states that must be exhaustive. For the feel and feedback of a single interaction, use `micro-interaction-spec`.
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。
Specify one micro-interaction completely — trigger, rules, feedback, loops, and modes. Use when handing a single interaction to engineering. For motion craft alone use `animation-principles`; for multi-state components use `state-machine`.
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 blueprint for hierarchical finite state machines (HSM) and pushdown automata for complex AI/character behaviors. Covers state stacks, sub-states, transition validation, and state context passing. Use when basic FSMs are insufficient OR implementing layered AI. Keywords state machine, HSM, hierarchical, pushdown automata, state stack, FSM, AI 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。
Bevy ECS skill for app states and per-entity state data. Keywords: Bevy, States, NextState, OnEnter.
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 implementing state machines in Godot — enum-based, node-based, and resource-based FSM patterns with trade-offs
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。
Document UI component states (current vs expected) with transitions
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 an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
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 LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when "langgraph, langchain agent, stateful agent, agent graph, react agent, agent workflow, multi-step agent, langgraph, langchain, agents, state-machine, workflow, graph, ai-agents, orchestration" mentioned.
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 designing and implementing intelligent game AI systems including behavior trees, finite state machines, GOAP, utility AI, pathfinding, steering behaviors, and perception systems. Specializes in creating believable, performant NPC behaviors that enhance player experience. Use when "game AI, NPC behavior, behavior tree, state machine for game, enemy AI, pathfinding, A* algorithm, navmesh, steering behavior, GOAP, utility AI, AI perception, combat AI, companion AI, boss AI, crowd simulation, flocking, game-ai, behavior-trees, pathfinding, npc, state-machines, goap, utility-ai, steering, perception" mentioned.
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 real-time game animation systems including skeletal animation, blend trees, state machines, inverse kinematics, root motion, procedural animation, and animation retargeting. Specializes in creating fluid, responsive character animation that balances visual quality with performance constraints. Use when "animation system, state machine, blend tree, skeletal animation, inverse kinematics, IK system, root motion, animation blending, character animation, animator controller, motion matching, animation retargeting, foot IK, look at IK, aim offset, animation montage, animation notify, additive animation, animation layers, procedural animation, animation, game-dev, character, state-machine, unity, unreal, godot, skeletal, rigging, motion" mentioned.
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。
Model complex UI behavior as finite state machines with states, events, and transitions.
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 adding character/enemy/game-flow states or NPC behaviour - explicit transition tables instead of flag soup, hierarchical and pushdown machines, behaviour trees per engine, navmesh pathfinding, AI tick budgets, and table-driven tests.
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。
Godot 4 有限状态机设计模式,包含状态基类、状态机管理、状态转换和输入处理。
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 sequential (stateful) logic circuits including latches, flip-flops, registers, counters, and finite state machines. Covers SR latch, D and JK flip-flops, binary/BCD/ring counters, and Mealy/Moore FSM design with clock signal and timing analysis. Use when a circuit must remember past inputs, count events, or implement a state-dependent control sequence.
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 designing, implementing, or debugging complex agentic workflows using state machine patterns. Keywords: state machine, durable execution, agent orchestration, graph-based agents, workflow checkpoints, C4 protocol.
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。
Interface-based state machine patterns for Unity game states, character controllers, and UI flows. Use when implementing game flow (menu -> gameplay -> game over), character states (idle -> run -> jump -> fall), AI behavior states, or UI screen transitions. Triggers on "state machine", "game states", "character states", "screen flow", "game flow", "add states to", "idle/run/jump", "menu flow", "AI states", "boss phases", or any task involving managing discrete states with transitions between them. Reads ProjectConfig.yaml -> architecture_pattern to adapt patterns for SO-first or DI-first.
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 machine patterns for Unity including hierarchical states, async transitions, and cleanup safety.
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。
Unity state and behavior system architecture. FSM, Hierarchical FSM, Behavior Trees, stack-based state machines, Animator-vs-code decisions, state machine testing. DECISION format: WHEN/DECISION/SCAFFOLD/GOTCHA. Based on Unity 6.3 LTS.
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 generating or editing diagrams, charts, visual assets, posters, UI mockups, product images, infographics, academic figures, comics, avatars, storyboards, brand boards, or image-edit workflows, especially when exported PNGs need visual QA and bounded self-repair. Prefer deterministic Mermaid/SVG/HTML/canvas sources for text-heavy diagrams; use HTML technical diagrams for browser-ready system blueprints, architecture, deployment topology, agent runtime, memory flow, before-after architecture, workflow, sequence, data-flow, lifecycle, runbook, PII/data-lineage, and state-machine diagrams. Do not use for ordinary UI polish without generated imagery.
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。
Run work as an explicit event-driven state machine executed by subagents. The orchestrator is the runtime from the canonical loop — `state, effects = init(machine); execute(effects); while state is active: event = nextEvent(); state, effects = transition(machine, state, event); execute(effects); return state.output`. All routing judgment is authored ONCE, at plan time, into a machine file (states, event alphabet, transition table, budgets, final states); at runtime the orchestrator does pure table lookups and dispatches effects — it never decides, never authors, never ingests artifacts. Subagent/sync protocol is the timeboxed-iterating one: role prompts scaffolded once to disk and dispatched BY PATH, an initialiser preamble every subagent reads first, a self-populating cheatsheet, per-unit files, tiny structured returns, independent measurement gate. Use when the user says "workmachine", "run this as a state machine", "state-machine this", or when a goal has a small number of clearly named phases with explicit outcomes (built / passed / failed / blocked) and you want the routing to be auditable rather than judged on the fly. For clock-driven loops use timeboxed-iterating; for wide graphs with judged edge criteria use workgraph.
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 publish-grade SVG+PNG technical diagrams (architecture, data flow, sequence, ER, state-machine, etc.) in 8 styles. Writes to tasks/visuals/. Needs rsvg-convert for PNG; else SVG-only.
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。