flovart

name	flovart
description	Use when Claude Code needs to operate Flovart as an agent-native media runtime. Flovart generates and manages images/videos through deterministic CLI commands. Claude Code handles scripts, storyboards, prompts, and planning. CLI is the universal interface.

Flovart Skill

Flovart is a deterministic media runtime. You are the planner. All operations go through npm run flovart:cli -- <command> --json.

Runtime Setup

1. npm run dev
2. Open Flovart in the browser when a command needs provider execution
3. npm run flovart:cli -- status --json

Without a browser, commands fall back to shadow runtime — state persists to disk and executes when the browser opens.

Rules

• Never ask the user to paste API keys. Use provider.begin-setup to open the browser UI.
• Do not add text nodes to the Flovart canvas. Canvas is media-only: images and videos.
• Use CLI as the only external interface. No protocol server or CDP port is required.
• Keep all tool calls explicit and JSON-safe.

Atomic CLI Commands

Status & Setup

Command	Args
status	—
doctor	--project-dir
init	--host claude|cursor|vscode|all
command.list	—

Provider & API Keys

Command	Args
provider.status	—
provider.begin-setup	--provider gemini|openai|custom --purpose image|video|both
provider.select-model	--image-model <id> --video-model <id> --text-model <id>
provider.test	--purpose image|video|both

Canvas — Media Elements

Command	Args
canvas.inspect	—
canvas.list-media	—
canvas.add-image	--href <data-url-or-url> --mime-type image/png [--name <name> --x 0 --y 0]
canvas.add-video	--href <data-url-or-url> --mime-type video/mp4 [--name <name>]
canvas.upload-image	--path <local-file-path> [--name <name>]
canvas.upload-video	--path <local-file-path> [--name <name>]
canvas.update-element	--id <id> --updates-json <json>
canvas.remove-element	--id <id>
canvas.select	--ids id1,id2
canvas.clear-media	—

Element Generation

Command	Args
element.create	--type image|video --name <name> [--x 0 --y 0 --href <url>]
element.update-prompt	--element-id <id> --text-prompt "<prompt>" [--model-id <id>]
element.assign-slot	--element-id <id> --target-element-id <id> --slot-role first_frame|style_ref|control_net|unassigned
element.ignite	--element-id <id>
element.watch	--element-id <id> [--timeout-ms 120000]

Generation (One-Shot)

Command	Args
generate.image	--prompt "<prompt>" [--aspect-ratio 16:9]
generate.images-batch	--file shots.json
generate.video	--prompt "<prompt>" [--source-image-ids id1,id2 --duration-sec 5 --aspect-ratio 16:9]
video.status	--job-id <id>

Workflow — Graph Operations

Command	Args
workflow.inspect	—
workflow.load	--file workflow.json or --workflow-json '<json>'
workflow.update-node	--node-id <id> --config-json '<json>'
workflow.run	[--scope workflow|node|from-here --node-id <id>]
workflow.plan-video	--prompt "<prompt>" [--count 3 --aspect-ratio 16:9 --duration-sec 5 --image-model flux-schnell --video-model kling-v2]

Planning & Discovery

Command	Args
batch.plan	--prompt "<prompt>" [--count 4 --aspect-ratio 16:9]
prompt.enhance	--prompt "<prompt>" [--style cinematic --mode image|video]
models.list	--purpose image|video|all
preferences.manage	--action get|set|reset|add-favorite
inspiration.search	--query <term> [--category <cat>]
inspiration.get	--id <id>

Workflows

Quick Image Generation

npm run flovart:cli -- generate.image --prompt "futuristic city at sunset" --json

Upload Local Media

npm run flovart:cli -- canvas.upload-image --path "C:\Users\me\Pictures\ref.png" --name "Reference" --json

Batch Storyboard

npm run flovart:cli -- batch.plan --prompt "product launch campaign" --count 4 --json
# save shots to file, edit prompts, then:
npm run flovart:cli -- generate.images-batch --file shots.json --json

Custom Video Workflow (Agent-Planned)

# 1. Generate a multi-shot video workflow graph
npm run flovart:cli -- workflow.plan-video --prompt "cyberpunk street chase" --count 4 --duration-sec 5 --json > workflow.json

# 2. Load the workflow into the canvas
npm run flovart:cli -- workflow.load --file workflow.json --json

# 3. Inspect
npm run flovart:cli -- workflow.inspect --json

# 4. Tweak a node's model
npm run flovart:cli -- workflow.update-node --node-id "shot-2-video" --config-json '{"model":"veo-3"}' --json

# 5. Run the whole graph
npm run flovart:cli -- workflow.run --scope workflow --json

Per-Node Model / API Key Control

# Set model on any workflow node
npm run flovart:cli -- workflow.update-node --node-id "shot-1-image" --config-json '{"model":"gpt-image-2","apiKeyRef":"key-abc123"}' --json

Shadow Runtime (No Browser)

CLI data commands use the local file-state runtime at %LOCALAPPDATA%\Flovart\shadow-runtime-state.json. Provider-backed generation requests are queued through .flovart/command-queue.json and execute when the Flovart browser app is open.

npm run flovart:cli -- status --json
# => { "ok": true, "runtime": "file-state", "data": { "runtime": "flovart-shadow-runtime", ... } }