Add WallCraft AI MVP scaffolding and documentation

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Jamie Miller
2026-02-06 07:48:40 +00:00
parent cabd4ecf66
commit 34da1bc90b
15 changed files with 524 additions and 0 deletions

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WallCraft AI Agents Collaboration Guide for WallCraft AI
Overview
- Purpose: Define how automated agents will plan, explore, and assist in building a cloud-driven AI workflow for FoundryVTT scene prep (walls, doors, windows), with a safe preview-first workflow.
- Scope: Plan, explore, and coordinate tasks across agent types; no direct code edits by agents, only plan and guidance unless explicitly executed by humans.
Agent Roles and Responsibilities
- General Planner (PlanAgent)
- Create high-level task plans, decompose features into concrete steps, and assign ownership.
- Explorer (ExploreAgent)
- Inspect repository structure, FoundryVTT APIs, and proposed module architecture.
- Code Searcher (CodesearchAgent)
- Look up API docs, FoundryVTT wall/scene data models, and related examples.
- Web Scout (WebSearchAgent)
- Retrieve current best practices, security considerations, and external docs relevant to cloud AI integration and similar Foundry workflows.
Interaction Protocol
- Requests and responses are exchanged as structured JSON envelopes.
- Each task has: task_id, objective, inputs, constraints, and expected outputs.
- All agents should statically log their actions to an in-app log or a dedicated journal entry for traceability.
Example envelope (high-level)
- Plan request
{
"task_id": "plan-001",
"role": "Planner",
"objective": "Define MVP milestones for AI Prep pipeline",
"inputs": { "scope": "FoundryVTT 13.0.351 MVP" },
"constraints": { "no destructive edits during planning": true }
}
- Plan response
{
"status": "ok",
"task_id": "plan-001",
"plan": [
"Create module scaffold with manifest.json",
"Implement Settings for cloud endpoint and provider",
"Add AI Prep UI (Scene toolbar) and preview layer",
"Define payload schema and fixed prompt template",
"Implement preview → manual adjust → apply workflow",
"Add logging and minimal docs"
],
"notes": "Keep MVP strictly non-destructive during preview; apply only after explicit confirmation."
}
Task Lifecycle and Phases
- Phase 0: Planning and scoping
- Phase 1: MVP scaffolding (module skeleton, settings, UI hooks)
- Phase 2: Cloud integration and preview rendering
- Phase 3: Apply flow (convert AI walls to Foundry walls)
- Phase 4: Safety, validation, and docs
- Phase 5: Optional enhancements (Doors/Windows refine, per-scene prompts, etc.)
Data Exchange and Contracts (see data-contracts.md)
- Use a fixed, provider-agnostic payload to cloud AI endpoint
- Validate AI responses against Foundry grid constraints before enabling apply
Quality and Safety
- Preview is mandatory before applying changes
- All actions should be auditable (chat log or journal entry)
- Validate that walls align to grid and do not collide with tokens
- Optional data redaction in settings for privacy-sensitive scenes
Documentation and Handoff
- Produce a short design doc, an API contract summary, and a quick-start guide
- Maintain change logs for major iterations and provider changes
4) data-contracts.md
AI Prep Data Contracts (Input to AI, and AI Output)
Input payload to cloud AI
- Schema (JSON)
{
"scene": { "id": "scene123", "name": "Test Scene" },
"gridSize": 32,
"walls": [
{ "c": [1,1,5,1], "type": "wall", "notes": "outer boundary" },
{ "c": [5,1,5,5], "type": "door", "notes": "entry" }
],
"tokens": [
{ "id": "tok1", "x": 3, "y": 3, "w": 1, "h": 1 }
],
"promptTemplate": "Fixed MVP prompt template string",
"providerMetadata": { "providerName": "OpenCodeCloud", "version": "v1" },
"previewOnly": true
}
AI output payload
- Schema (JSON)
{
"walls": [
{ "c": [1,1,6,1], "type": "wall", "notes": "perimeter suggestion" },
{ "c": [6,1,6,6], "type": "door", "notes": "future entry" }
],
"notes": [ "Preview generated" ],
"validationHints": [ "Walls may cross token area; adjust endpoints" ],
"previewOnly": true
}
Notes
- All coordinates are grid-aligned integers.
- Unknown fields from provider can be ignored by the client.
- If previewOnly is true, apply is disabled until user explicitly enables it.
5) api-contract.md
Cloud AI Endpoint Contract (example)
Endpoint
- POST https://api.youraihost.com/ai/map-prep
Headers
- Authorization: Bearer <apiToken>
- Content-Type: application/json
Request body (see data-contracts.md)
- {
"scene": { "id": "...", "name": "..." },
"gridSize": 32,
"walls": [...],
"tokens": [...],
"promptTemplate": "...",
"providerMetadata": { "providerName": "...", "version": "..." },
"previewOnly": true
}
Response
- 200 OK
- {
"walls": [...],
"notes": ["Preview generated"],
"validationHints": [...],
"previewOnly": true
}
- 4xx/5xx responses
- { "error": "invalid_payload", "message": "..." }
- { "error": "auth_failed", "message": "Invalid API token" }
Security and Privacy
- Use HTTPS; support short-lived tokens
- Minimize data; avoid sending unrelated scene data unless required
- Log access on the server side; provide per-request trace IDs
6) onboarding.md
Onboarding for WallCraft AI Contributors
Overview
- This document helps new contributors get up to speed on the WallCraft AI MVP project.
Getting started
- Prerequisites: FoundryVTT v13.0.351, node environment for building modules, access to cloud AI endpoint
- Repository layout: modules/wallcraft-ai/ with module.json and src/
- Key files to know:
- module.json: module manifest
- src/AIPrep.js: main module entry
- src/AIEndpoint.js: HTTP client for cloud AI
- src/PreviewLayer.js: canvas overlay logic
- src/SettingsPanel.js: UI to configure endpoint/token/provider
- src/UIFlow.js: dialog and adjustment UI
Development workflow
- Plan first: use agents.md to outline tasks
- Implement in small, testable increments
- Use non-destructive previews first; require explicit apply
- Write minimal tests or manual checks for payload shaping and wall conversion
Conventions
- Naming: consistent with FoundryVTT APIs (Wall, Door, Window, Scene)
- Data models: grid-aligned coordinates, tokens as bounding boxes
- Logging: messages go to chat or a dedicated journal entry
Testing and validation
- Manual test plan: create a sample scene, run AI Prep, verify preview, adjust, apply, verify persistence
- Edge cases: empty AI response, missing fields, invalid coordinates
Deployment and updates
- Document how to deploy updates to cloud endpoint if users host their own
- Provide migration notes for API changes (backward compatibility guidance)
7) glossary.md
WallCraft AI Glossary
- FoundryVTT: The virtual tabletop platform being extended.
- Scene: A map/workspace in FoundryVTT where walls, tokens, and other elements live.
- Wall: A linear obstacle segment; may be solid, a door, or a window.
- Door/Window: Wall segments with special types; may require swing/hinge data later.
- GridSize: The pixel size of a single tile on the scene grid.
- Preview: A non-destructive overlay showing AI-suggested walls before applying them.
- MVP: Minimum Viable Product.
- API Token: Secret used to authorize requests to the cloud AI endpoint.
8) quick-start.md
WallCraft AI Quick Start (MVP)
What youll get
- A cloud-driven FoundryVTT MVP to generate walls (including doors/windows) for the current scene.
- Non-destructive preview with manual adjustments before applying.
Setup
- Install FoundryVTT module (WallCraft AI) for FoundryVTT v13.0.351
- Configure cloud endpoint URL and API token in Settings
- Ensure the cloud AI endpoint is reachable via HTTPS
How to use
- In FoundryVTT, open a scene and click the WallCraft AI Prep button in the Scene toolbar
- The module collects scene data and sends a fixed prompt to the cloud AI
- See a translucent preview of AI-generated walls
- Use the adjustment panel to tweak endpoints or types if needed
- Click Apply to persist walls to the scene
- Review chat/journal log for traceability
Notes
- Batching and multi-scene processing are not part of MVP; plan for future sprints if you want to scale.
- Security: only necessary scene data is sent; token remains with you.
Next steps
- If youd like, I can generate concrete starter patches (module.json + a minimal AIPrep.js skeleton and the SettingsPanel), plus the exact payload shapes ready to patch into your repo. I can also tailor naming and endpoint paths to your preferred conventions.
9) structure.md
WallCraft AI Default File Structure
- /modules/wallcraft-ai/
- module.json
- /src/
- AIPrep.js
- AIEndpoint.js
- PreviewLayer.js
- SettingsPanel.js
- UIFlow.js
- /agents.md
- /data-contracts.md
- /api-contract.md
- /onboarding.md
- /glossary.md
- /quick-start.md
This structure keeps the core module logic separated from the documentation and keeps the docs versioned with the module code.

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Cloud AI Endpoint Contract (example)
Endpoint
- POST https://api.youraihost.com/ai/map-prep
Headers
- Authorization: Bearer <apiToken>
- Content-Type: application/json
Request body (see data-contracts.md)
- {
"scene": { "id": "...", "name": "..." },
"gridSize": 32,
"walls": [...],
"tokens": [...],
"promptTemplate": "...",
"providerMetadata": { "providerName": "...", "version": "..." },
"previewOnly": true
}
Response
- 200 OK
- {
"walls": [...],
"notes": ["Preview generated"],
"validationHints": [...],
"previewOnly": true
}
- 4xx/5xx responses
- { "error": "invalid_payload", "message": "..." }
- { "error": "auth_failed", "message": "Invalid API token" }
Security and Privacy
- Use HTTPS; support short-lived tokens
- Minimize data; avoid sending unrelated scene data unless required
- Log access on the server side; provide per-request trace IDs

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AI Prep Data Contracts (Input to AI, and AI Output)
Input payload to cloud AI
- Schema (JSON)
{
"scene": { "id": "scene123", "name": "Test Scene" },
"gridSize": 32,
"walls": [
{ "c": [1,1,5,1], "type": "wall", "notes": "outer boundary" },
{ "c": [5,1,5,5], "type": "door", "notes": "entry" }
],
"tokens": [
{ "id": "tok1", "x": 3, "y": 3, "w": 1, "h": 1 }
],
"promptTemplate": "Fixed MVP prompt template string",
"providerMetadata": { "providerName": "OpenCodeCloud", "version": "v1" },
"previewOnly": true
}
AI output payload
- Schema (JSON)
{
"walls": [
{ "c": [1,1,6,1], "type": "wall", "notes": "perimeter suggestion" },
{ "c": [6,1,6,6], "type": "door", "notes": "future entry" }
],
"notes": [ "Preview generated" ],
"validationHints": [ "Walls may cross token area; adjust endpoints" ],
"previewOnly": true
}
Notes
- All coordinates are grid-aligned integers.
- Unknown fields from provider can be ignored by the client.
- If previewOnly is true, apply is disabled until user explicitly enables it.

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WallCraft AI Glossary
- FoundryVTT: The virtual tabletop platform being extended.
- Scene: A map/workspace in FoundryVTT where walls, tokens, and other elements live.
- Wall: A linear obstacle segment; may be solid, a door, or a window.
- Door/Window: Wall segments with special types; may require swing/hinge data later.
- GridSize: The pixel size of a single tile on the scene grid.
- Preview: A non-destructive overlay showing AI-suggested walls before applying them.
- MVP: Minimum Viable Product.
- API Token: Secret used to authorize requests to the cloud AI endpoint.

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{
"name": "wallcraft-ai",
"title": "WallCraft AI",
"description": "Cloud-driven, provider-agnostic AI prep for FoundryVTT scenes (walls including doors and windows) with a safe preview-first workflow.",
"version": "0.1.0",
"author": "OpenCode",
"minimumCoreVersion": "13.0.0",
"compatibleCoreVersion": "13.*",
"esmodules": true,
"scripts": [
"src/AIPrep.js",
"src/AIEndpoint.js",
"src/PreviewLayer.js",
"src/SettingsPanel.js",
"src/UIFlow.js"
],
"url": "https://example.com/wallcraft-ai",
"license": "MIT"
}

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Onboarding for WallCraft AI Contributors
Overview
- This document helps new contributors get up to speed on the WallCraft AI MVP project.
Getting started
- Prerequisites: FoundryVTT v13.0.351, node environment for building modules, access to cloud AI endpoint
- Repository layout: modules/wallcraft-ai/ with module.json and src/
- Key files to know:
- module.json: module manifest
- src/AIPrep.js: main module entry
- src/AIEndpoint.js: HTTP client for cloud AI
- src/PreviewLayer.js: canvas overlay logic
- src/SettingsPanel.js: UI to configure endpoint/token/provider
- src/UIFlow.js: dialog and adjustment UI
Development workflow
- Plan first: use agents.md to outline tasks
- Implement in small, testable increments
- Use non-destructive previews first; require explicit apply
- Write minimal tests or manual checks for payload shaping and wall conversion
Conventions
- Naming: consistent with FoundryVTT APIs (Wall, Door, Window, Scene)
- Data models: grid-aligned coordinates, tokens as bounding boxes
- Logging: messages go to chat or a dedicated journal entry
Testing and validation
- Manual test plan: create a sample scene, run AI Prep, verify preview, adjust, apply, verify persistence
- Edge cases: empty AI response, missing fields, invalid coordinates
Deployment and updates
- Document how to deploy updates to cloud endpoint if users host their own
- Provide migration notes for API changes (backward compatibility guidance)

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[]

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[
{"id":"t-1","content":"Initialize module skeleton (module.json) and scaffolding","status":"in_progress","priority":"high"},
{"id":"t-2","content":"Implement SettingsPanel for endpoint/token/provider","status":"pending","priority":"high"},
{"id":"t-3","content":"Implement AIPrep.js to collect scene data and build payload","status":"pending","priority":"high"},
{"id":"t-4","content":"Implement AIEndpoint.js to call cloud API and handle responses","status":"pending","priority":"high"},
{"id":"t-5","content":"Implement PreviewLayer.js for non-destructive previews","status":"pending","priority":"high"},
{"id":"t-6","content":"Implement UIFlow.js to drive MVP flow","status":"pending","priority":"medium"},
{"id":"t-7","content":"Wire up Apply logic to convert AI walls to Foundry walls","status":"pending","priority":"high"},
{"id":"t-8","content":"Create documentation: quick-start, data/api contracts","status":"pending","priority":"medium"},
{"id":"t-9","content":"Add basic tests/manual validation plan","status":"pending","priority":"medium"},
{"id":"t-10","content":"Polish error handling, security notes","status":"pending","priority":"low"}
]

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WallCraft AI Quick Start (MVP)
What youll get
- A cloud-driven FoundryVTT MVP to generate walls (including doors/windows) for the current scene.
- Non-destructive preview with manual adjustments before applying.
Setup
- Install FoundryVTT module (WallCraft AI) for FoundryVTT v13.0.351
- Configure cloud endpoint URL and API token in Settings
- Ensure the cloud AI endpoint is reachable via HTTPS
How to use
- In FoundryVTT, open a scene and click the WallCraft AI Prep button in the Scene toolbar
- The module collects scene data and sends a fixed prompt to the cloud AI
- See a translucent preview of AI-generated walls
- Use the adjustment panel to tweak endpoints or types if needed
- Click Apply to persist walls to the scene
- Review chat/journal log for traceability
Notes
- Batching and multi-scene processing are not part of MVP; plan for future sprints if you want to scale.
- Security: only necessary scene data is sent; token remains with you.
Next steps
- If youd like, I can generate concrete starter patches (module.json + a minimal AIPrep.js skeleton and the SettingsPanel), plus the exact payload shapes ready to patch into your repo. I can also tailor naming and endpoint paths to your preferred conventions.

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// Lightweight HTTP client for the cloud AI endpoint
export async function aiPrepRequest(payload, endpoint, token) {
const resp = await fetch(endpoint, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': token ? `Bearer ${token}` : ''
},
body: JSON.stringify(payload)
});
if (!resp.ok) {
const err = await resp.text();
throw new Error(`AI prep request failed: ${resp.status} ${resp.statusText} - ${err}`);
}
return resp.json();
}

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// WallCraft AI: Minimal MVP skeleton for FoundryVTT module (WallCraft AI)
import { SettingsPanel } from './SettingsPanel.js';
import { startAIPrepFlow } from './UIFlow.js';
export function initWallCraftAI() {
Hooks.on('ready', async function () {
if (!game.user?.isGM) return;
// Simple guidance dialog for first-time setup
new Dialog({
title: 'WallCraft AI',
content: '<p>WallCraft AI is ready. Use Settings to configure the cloud endpoint, then start the MVP prep flow.</p>',
buttons: {
settings: { label: 'Settings', callback: () => SettingsPanel.open() },
start: { label: 'Start MVP', callback: () => startAIPrepFlow() }
},
default: 'start'
}).render(true);
});
}
Hooks.once('init', () => {
// Initialize basic settings with sane defaults if needed
// Actual settings are declared in SettingsPanel
initWallCraftAI();
});

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// Lightweight non-destructive preview layer for WallCraft AI
export class PreviewLayer {
static drawWalls(scene, walls) {
// Placeholder: In a full implementation this would render translucent wall overlays
console.log('[WallCraft AI] Preview walls:', walls);
}
static clear() {
console.log('[WallCraft AI] Clearing previews');
}
}

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// Settings UI for WallCraft AI (endpoint, token, provider)
export class SettingsPanel {
static open() {
const html = `
<form id="wca-settings-form">
<div>
<label>Endpoint URL</label><br/>
<input type="text" id="wca-endpoint" style="width:100%" value="https://api.youraihost.com" />
</div>
<div>
<label>API Token</label><br/>
<input type="password" id="wca-token" style="width:100%" />
</div>
<div>
<label>Provider Name</label><br/>
<input type="text" id="wca-provider" style="width:100%" value="OpenCodeCloud" />
</div>
</form>`;
new Dialog({
title: 'WallCraft AI Settings',
content: html,
buttons: {
save: { label: 'Save', callback: (dlg) => {
const endpoint = dlg.find('#wca-endpoint').val();
const token = dlg.find('#wca-token').val();
const provider = dlg.find('#wca-provider').val();
// Persist via Foundry settings
game.settings.set('wallcraft-ai', 'endpointUrl', endpoint);
game.settings.set('wallcraft-ai', 'apiToken', token);
game.settings.set('wallcraft-ai', 'providerName', provider);
}}
},
default: 'save'
}).render(true);
}
}

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// Basic UI flow helpers for WallCraft AI (MVP)
export function startAIPrepFlow() {
new Dialog({
title: 'WallCraft AI Prep (MVP)',
content: '<p>Trigger cloud AI to generate wall layout for the current scene. This is a placeholder MVP flow.</p>',
buttons: {
ok: { label: 'OK' }
}
}).render(true);
}

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WallCraft AI Default File Structure
- /modules/wallcraft-ai/
- module.json
- /src/
- AIPrep.js
- AIEndpoint.js
- PreviewLayer.js
- SettingsPanel.js
- UIFlow.js
- /agents.md
- /data-contracts.md
- /api-contract.md
- /onboarding.md
- /glossary.md
- /quick-start.md
This structure keeps the core module logic separated from the documentation and keeps the docs versioned with the module code.