Graph World

GraphOS Skill: graph-world

Design world logic in GraphOS with a node-first architecture for any game or application.

This skill depends on graph-management for graph inspection and transaction apply APIs.

Use graph-world-ts after graph validation is complete whenever the task moves into npm/TypeScript project bootstrap, generated code integration, or runtime implementation of Systems and EventSystems.

Node Semantics

• World: Single root context of the whole model. The World node name is fixed to World.
• Context: Hierarchical domain/data model node under World or Context. Context belongs to the logical/data layer, not the presentation layer, but should expose the state that the View layer needs to observe. Context also has built-in storage semantics, so logic should prefer reusing existing Context instances/state before creating new ones.
• Variant: Typed variable definition under World or Context. Variant is the default design surface for persistent/stored runtime data.
• System: Lifecycle logic node under World or Context. Temporary cache or ephemeral working state should be handled inside the owning System rather than modeled as stored graph data.
• Event: World-level event definition. Event naming must encode its layer boundary: names starting with On represent presentation-layer events and should keep payloads minimal, ideally no payload; names starting with Logic represent internal logic-layer events and are reserved for world/domain orchestration inside the logic layer.
• EventSystem: Event-driven handler under Event.

Event Naming Boundary (Mandatory)

• Use the On prefix for presentation-layer events only.
• On... events represent signals emitted toward or from the View/presentation layer and should use the smallest payload possible, preferably no payload when the View can derive state from observed Context data.
• Use the Logic prefix for internal logic-layer events only.
• Logic... events are for domain/runtime coordination inside the world model and should not be used as presentation-facing event names.
• Do not mix the two semantics in a single event name. If an event crosses both concerns, split it into a logic event and a separate presentation event.

Configuration Boundary (Mandatory)

• Graph defines runtime logic structure only: World/Context/Variant/System/Event/EventSystem and their ownership/trigger relations.
• Do not model configuration-only structures in Graph (for example config catalogs, environment profiles, tuning tables, feature-flag maps, platform build config).
• During code generation and runtime implementation, design configuration structures in code (for example src/config.ts, typed constants/interfaces, loaders/adapters), and keep them outside Graph topology.
• If a field is needed only to configure implementation and is not domain runtime state, keep it in code config instead of Graph Variant.

When to Use

• You are designing a new game/app world model from scratch.
• You need to convert business domains into nested Context trees.
• You need typed data variables (Variant) before writing lifecycle logic.
• You need event-driven initialization or runtime flows (for example game startup).

Preconditions

1. Load and use graph-management skill first.
2. Read available node types and current graph state before mutation.
3. Use one coherent transaction per design step when possible.
4. Enforce root naming constraint: the World node name is fixed to 'World'.

Simulator Log Inspection

Use this when the world plugin simulator is available and you need to inspect actual runtime event flow instead of relying only on static graph structure.

1. Start or drive the simulator until the target branch or scenario has executed.
2. Query /api/world/log through the GraphOS runtime.
3. Read the default response first to inspect all logs up to the current simulator time.
4. When investigating one branch, narrow the query with startTime and endTime to isolate the simulated interval.
5. If /api/world/log returns a large payload, generate a script to analyze the data instead of relying on manual inspection.

Expected behavior of /api/world/log:

• No query parameters: returns logs at simulated times <= current.
• startTime only: returns logs in [startTime, current].
• endTime only: returns logs in (-∞, endTime].
• startTime and endTime: returns logs in [startTime, endTime].

When the /api/world/log response is large:

• Generate a small analysis script to parse, filter, group, and summarize the log records.
• Prefer script output over raw full-log printing; emit condensed summaries such as event counts, time ranges, target Context ids, and suspicious error patterns.
• Use the script to isolate the exact branch, Event, System, or Context mutation under investigation before making graph or runtime changes.
• Keep the script focused on the current debugging target and make its filters explicit, for example by event name, log type, Context id, or simulated time window.
• If needed, iterate by refining the script filters rather than repeatedly reading the full /api/world/log payload manually.

Use simulator log inspection for:

• Verifying that expected spawn, change, despawn, and event records were produced.
• Confirming that a System or EventSystem changed the intended Context data during the expected simulated interval.
• Narrowing a runtime defect before patching graph topology or generated logic.

Simulator Control API

Use these endpoints to control simulator execution via HTTP. All three accept a POST request and return { ok: true } on success.

• GET /api/world/state — Get simulator current state. Returns { duration, current, state, scale, fps }. state is one of 'running' | 'paused' | 'loading' | 'stopped'.
• POST /api/world/start — Start the simulator clock from time zero. Begins time progression and lifecycle logic execution.
• POST /api/world/pause — Pause the simulator clock. Log recording continues but time progression stops.
• POST /api/world/resume — Resume the simulator clock from where it was paused.
• POST /api/world/reset — Reset the simulator to its initial state, clearing all runtime state and logs.
• POST /api/world/event — Send a client event into the simulator. The request body must conform to IEvent interface. The simulator dispatches it through the event system as if it originated from a connected client.

  interface IEvent {
      type: string;
      [key: string]: unknown;
  }
  

  Example: { "type": "MyEvent", ...additional fields as needed }

Modification Rules (Mandatory Order)

These rules are hard constraints for any change workflow:

1. Data model and data logic changes must be applied to Graph first.
   • Complete required Context/Variant/System/Event/EventSystem updates in Graph before writing downstream code/docs/tasks.
2. Validate Graph logic is closed-loop immediately after Graph changes.
   • Run the Step 4 closure checks and ensure all closure dimensions pass.
3. Only after closed-loop validation passes, proceed to any other tasks.
   • If closure fails, return to Graph patching first; do not continue with non-Graph work.
4. After every successful graph change, update gen/README.md with a change record.
   • Record what was added/modified/removed and why.
   • Append to the change log section; do not overwrite previous records.
5. After every successful graph change, update gen/GRAPH.md with the complete current process diagram and closure checkpoints.
   • Keep the diagram in sync with the actual Step 0-6 workflow.
   • Validate that the diagram remains closed-loop (failed checks route back to patch steps).

Procedure

Step 0: Read Current State

1. Call get_available_node_types to validate node schemas.
2. Call get_graph_description to identify current root, contexts, and gaps.
3. If extending an existing area, call get_graph_node on the focus node.

Completion check:

• You know whether a World node already exists.
• You confirmed the World root node name is exactly 'World'.
• You know where new Context/Variant/System/Event nodes should be attached.

Step 1: Build Data Model and Variants

Goal: create the structural model first, then type its data.

1. Ensure exactly one World root exists.
   • The root node name must be exactly World; do not rename it or create alternative root names.
2. Create Context tree by domain boundaries:
   • Broad to specific: e.g. Gameplay -> Player -> Inventory.
   • Keep sibling contexts cohesive and low-coupling.
3. Under each relevant World/Context, add Variant nodes:
   • Set name with stable semantic naming.
   • Set type from string|float|integer|boolean|JSONSchema.
   • If type=JSONSchema, provide jsonSchema with required fields.
   • Mark required only for truly mandatory runtime data.
4. Apply the transaction and re-read graph.

Decision points:

• Use Context when modeling a domain boundary or ownership scope.
• Use Variant when modeling typed data inside a scope, especially when the requirement includes storage/persistence.
• Prefer JSONSchema only for structured objects; otherwise use primitive types.
• If data must survive as part of the graph-defined state, design it as a Variant.
• If data is only a temporary cache, intermediate computation result, or frame-local working set, keep it inside the relevant System instead of adding a Variant.
• If data is configuration-only (build/runtime tuning, environment selection, feature flags, generator options), do not define it in Graph; define it in code configuration during generation/implementation.
• Graph design should contain logical/domain state only, not presentation-layer widgets, styles, animations, or rendering concerns.
• Design Context and its Variants so the View layer can react to data changes through observation/binding.
• If the View depends on explicit runtime states such as loading, selected, active, disabled, visible, phase, or mode, model those as logical state in Context/Variant rather than leaving them implicit in the presentation layer.

Completion check:

• Every core domain has a Context owner.
• Every runtime-critical datum has a Variant with explicit type.
• No orphan Variants without a clear World/Context parent.

Step 2: Define Systems Based on the Data Model

Goal: bind lifecycle behavior to existing data model scopes.

1. For each behavior unit, create a System under its owning World/Context.
2. Define required lifecycle entry points by implementation contract:
   • spawn, despawn, update, change.
3. Document each implemented lifecycle method with clear intent, trigger, and target data scope.
4. Ensure system responsibilities align with nearby Context/Variant ownership.
5. Apply and verify topology.

Decision points:

• Place System at the nearest scope that owns the data it mutates.
• Use Spawn for initialization, Update for recurring logic, Change for reactive sync, Despawn for cleanup.
• Split a System when a single node spans unrelated responsibilities.
• System implementation should contain no presentation-layer logic (rendering, styling, animation, UI orchestration).
• System logic should be driven by Context/Variant state and domain rules only.
• Keep temporary cache data internal to the owning System; do not promote cache-only state into graph Variants unless it must be stored as part of the domain model.

Completion check:

• Each implemented lifecycle method has a matching description.
• Systems are attached to the correct World/Context scope.
• No lifecycle method exists without a clear trigger and data target.

Implementation handoff:

• After Step 4 passes, use graph-world-ts to implement concrete TypeScript System code, startup bootstrap wiring, generated type integration, and src/app.ts registration.

Step 3: Define Events and EventSystems

Goal: model event-driven flows after data and lifecycle foundations are stable.

1. Under World, create Event nodes for key domain events:
   • Examples: GameStarted, UserRegistered, SessionRestored.
2. If event payload is needed, attach Variant nodes under each Event.
3. Under each Event, create EventSystem handlers:
   • Describe how handlers create/init/update Context instances.
4. Apply transaction and verify event-to-handler completeness.

Decision points:

• Create an Event for cross-context or explicit trigger boundaries.
• Use EventSystem when handling should be decoupled from per-frame System logic.
• For bootstrap flows, prefer an explicit startup/boot event plus handler.
• For UI-facing events, keep the Event data model as small as possible and prefer defining no payload fields unless data is strictly required.
• Name presentation-layer events with the On prefix and keep them signal-like whenever possible.
• Name internal logic-layer events with the Logic prefix and use them for domain orchestration rather than View-facing notifications.

Completion check:

• Every critical trigger has an Event.
• Every Event has at least one intended EventSystem handler (or explicitly documented as future work).
• Event payload Variants match handler input expectations.

Implementation handoff:

• After Graph trigger chains are validated, use graph-world-ts to implement concrete TypeScript EventSystem handlers, regenerate ./gen/World types, and wire registrations in src/app.ts.

Step 4: Closed-Loop Validation and Completion

Goal: verify the model is end-to-end closed-loop; if not, patch missing links and re-validate.

1. Run full validation after Step 1-3:
   • Re-run get_graph_description and compare expected topology with actual graph.
   • Optionally inspect key nodes with get_graph_node (World, core Contexts, bootstrap Event).
2. Validate closure dimensions:
   • Structural closure: single World root, no orphan Context/Variant/System/Event/EventSystem.
   • Data closure: each critical runtime datum exists as typed Variant and has owner scope.
   • Behavior closure: each implemented lifecycle method has a concrete description and target data.
   • Trigger closure: bootstrap and key domain triggers map to Event -> EventSystem -> target Context updates.
   • Transaction closure: all apply results are successful, or retries resolved partial failures.
3. If any closure check fails, classify and patch gaps in one focused transaction batch:
   • Missing structure/data -> go back to Step 1.
   • Missing lifecycle method coverage -> go back to Step 2.
   • Missing event trigger/handler chain -> go back to Step 3.
4. Re-run closure validation until all dimensions pass.
5. Produce final verification summary:
   • Added nodes/edges.
   • Remaining deferred items (if any) with explicit reason.
   • Confirmation that the model is closed-loop and ready for next iteration.

Completion check:

• All five closure dimensions pass.
• No unresolved critical gap remains.
• Final graph description matches intended domain design.

Step 5: Update gen/README.md Change Log

Goal: persist a human-readable record of every graph mutation session.

1. Open (or create) gen/README.md.
2. Append a new change record under a ## Change Log section using the format below:

### YYYY-MM-DD — <short summary>

**Added**
- <node type> `<node name>` under `<parent>`: <reason>

**Modified**
- <node type> `<node name>`: <what changed and why>

**Removed**
- <node type> `<node name>`: <reason>

**Notes**
- <any closure gaps deferred, design decisions, or follow-up items>

3. Do not overwrite previous records — always append.
4. Keep each entry concise (one line per node change is sufficient).

Completion check:

• gen/README.md exists and contains an up-to-date change record for this session.
• All added/modified/removed nodes are listed.
• Deferred items or known gaps are noted.

Step 6: Update gen/GRAPH.md Full Flow Diagram

Goal: keep an executable process diagram artifact that reflects the current workflow and closure loop.

1. Open (or create) gen/GRAPH.md.
2. Maintain one complete Mermaid flowchart for the end-to-end process:
   • Include Step 0 to Step 6.
   • Include closure dimensions and retry loops for failed checks.
3. After each graph mutation session, update the diagram if any step, gate, or retry path changed.
4. Validate closed-loop correctness in the diagram:
   • Any failed closure/gate must route back to the correct patch step.
   • Success path must end at final verification summary.

Completion check:

• gen/GRAPH.md exists and contains the latest complete flowchart.
• The flowchart includes all active steps (0-6) and retry branches.
• Diagram closure is verified: no broken success/failure path and no missing back-edge.

Quality Gates (Final Review)

1. Structure gate: exactly one World root, its name is exactly 'World', and the Context tree is coherent.
2. Type gate: Variants are typed correctly; JSONSchema nodes contain valid schema text.
3. Ownership gate: Systems and Variants are attached to the scope that owns their data.
4. Event gate: Event/EventSystem pairs cover bootstrap and key domain triggers.
5. Verification gate: re-run get_graph_description after each apply and confirm expected node/edge deltas.
6. Diagram gate: gen/GRAPH.md is updated and reflects the current closed-loop workflow.
7. Config boundary gate: Graph contains no configuration-only structure; configuration design is implemented in generated/runtime code.

Suggested Prompt Inputs

• "Design a roguelike game world with player, map, combat, and bootstrap event flow."
• "Build an e-commerce world model with catalog/order/payment contexts and event-driven order creation."
• "Create a smart-home app model with device contexts, lifecycle systems, and device-connected event handling."

Reference Example

skills/graph-world/World.graph.json is a complete, real-world graph for a Merge Chicken tower-defense game. Use it as a concrete reference when designing new worlds.

Structure Overview

World
└── Game (Context)          — shared game data
    ├── time (float)        — game time (seconds)
    ├── gold (integer)      — gold coins
    ├── wave (JSONSchema)   — current enemy wave {value, state, start_time}
    ├── egg (JSONSchema)    — egg cooldown config {time, cooldown, ...}
    ├── buy (JSONSchema)    — buy-chicken config {gold, increaseGold, ...}
    ├── heal (JSONSchema)   — heal config {gold, value}
    ├── health (JSONSchema) — global game health {value, max}
    ├── grid (JSONSchema)   — map grid {cols, rows, cell_size}
    ├── reward (JSONSchema) — claim-reward state
    ├── status (string)     — game status: none/running/paused/failed/success
    ├── Ally (Context)      — allied units (chickens)
    │   ├── level (integer)
    │   ├── attack (JSONSchema)  — {damage, speed, radius}
    │   ├── skin (string)
    │   ├── pos (JSONSchema)     — grid integer position {x, y}
    │   ├── ally_gold (Variant)  — chicken gold-production config
    │   ├── AllyAttackSystem     — launch attacks and shoot bullets based on attack data
    │   └── AllyGoldSystem       — periodically reward gold; higher level yields more gold
    ├── Enemy (Context)     — enemy units (dogs)
    │   ├── level, attack, health, move (JSONSchema)
    │   ├── skin (string), state (string: idle/walk/attack)
    │   ├── pos (JSONSchema)     — world float position {x, y}
    │   └── EnemyMoveSystem      — movement + attack-range check + self-destruct logic
    ├── Bullet (Context)    — bullets
    │   ├── damage, speed, max_count, radius (float/integer)
    │   ├── pos, dst (JSONSchema) — world float position
    │   ├── skin (integer)
    │   └── BulletMoveSystem     — bullet movement + enemy collision + attack logic
    ├── WaveSystem               — enemy wave spawn scheduling
    └── GameSystem               — initialize Game singleton, config-driven

Events (under World):
  Merge            → MergeEventSystem           — move / swap / merge chickens
  Egg              → EggEventSystem             — spawn chicken (free)
  Buy              → BuyEventSystem             — buy chicken (costs gold)
  Heal             → HealEventSystem            — restore game health
  IncreaseHealth   → IncreaseHealthEventSystem  — permanently increase max health
  Toast            → (tag, message)             — notification message
  Pause            → PauseEventSystem           — pause game
  Resume           → ResumeEventSystem          — resume game
  Reset            → ResetEventSystem           — restart after defeat (clear enemies + restore 50% health)
  ClaimReward      → ClaimRewardEventSystem     — claim stage-clear reward (multiplier supported)

Key Design Patterns in This Example

1. JSONSchema for structured data: Use JSONSchema Variant type when a field groups related sub-fields (e.g., attack = {damage, speed, radius}). Use primitive types (float, integer, string) for scalar values.
2. Config-driven Systems: GameSystem initializes a singleton Game context and reads all configurable parameters (costs, cooldowns, scaling) from Variant fields, never hard-coding values.
3. Singleton Context access: Systems and EventSystems always fetch the Game context by fixed id (getGameById('id')), not by positional child lookup.
4. Event payload minimalism: Events like Merge carry only the minimum required payload (ally_id, dst). The handler derives remaining state from Context.
5. Ephemeral state in System cache: Frame-local working sets (bullet-enemy collision candidates, move targets per frame) live in System closure scope, not as graph Variants.
6. Wave difficulty scaling: WaveSystem reads wave.value to scale enemy count and stats — all scaling parameters are configurable Variants, not embedded constants.
7. Reset flow: ResetEventSystem handles Reset event by despawning all Enemy and Bullet contexts, restoring health by a configurable percentage, and re-triggering wave spawn after a wait period.

Execution Notes

• Prefer atomic mutation batches with apply_graph_transaction.
• If partial success occurs, inspect errors and retry only failed intent.
• Keep node ids stable for iterative evolution.

Complete Process Diagram

flowchart TD
   A[Start: load graph-world skill] --> B[Preconditions\nload graph-management\nread node types + graph state]
   B --> C[Step 0\nRead Current State]
   C --> D[Step 1\nBuild Context tree + Variants]
   D --> E{Step 1 complete?\nno orphan data\nall key variants typed}
   E -- No --> D
   E -- Yes --> F[Step 2\nDefine Systems]
   F --> G{Step 2 complete?\nlifecycle methods + intent docs\nownership aligned}
   G -- No --> F
   G -- Yes --> H[Step 3\nDefine Events + EventSystems]
   H --> I{Step 3 complete?\ncritical events covered\nhandler chain defined}
   I -- No --> H
   I -- Yes --> J[Step 4\nClosed-Loop Validation]

   J --> K{Structure closure?\n(single World, no orphans)}
   K -- No --> D
   K -- Yes --> L{Data closure?\n(typed variants + owner scope)}
   L -- No --> D
   L -- Yes --> M{Behavior closure?\n(system timing -> descriptions -> data target)}
   M -- No --> F
   M -- Yes --> N{Trigger closure?\n(Event -> EventSystem -> Context update)}
   N -- No --> H
   N -- Yes --> O{Transaction closure?\n(apply success/retry resolved)}
   O -- No --> P[Inspect errors\nretry failed intent only]
   P --> J
   O -- Yes --> Q[Quality Gates Final Review]
   Q --> R{All gates passed?}
   R -- No --> J
   R -- Yes --> T[Step 5\nUpdate gen/README.md change log]
   T --> U[Step 6\nUpdate gen/GRAPH.md full flowchart\nand verify diagram closed-loop]
   U --> S[Output final verification summary\nClosed-loop model complete]