genmedia-workflow

name	genmedia-workflow
description	Design and execute multi-step media workflows with genmedia. Use this for pipelines that combine planning, generation, editing, image or video utilities, audio, subtitles, batching, and final delivery manifests.

Genmedia workflow production

Runtime: All endpoint calls run via the genmedia CLI. See the genmedia skill for command syntax; run genmedia init once if not yet installed.

Use this skill when a single model call is not enough. A workflow is a planned sequence of genmedia calls with clear inputs, outputs, dependencies, and quality checks.

Load references as needed:

• references/pipeline-patterns.md
• references/node-rules.md
• references/utility-endpoints.md
• references/recipes.md
• model-routing for creative model defaults

Use model-routing for default creative model choices. Still inspect schemas, check pricing when cost matters, and use exact endpoint fields.

Inputs to collect

Ask only for missing information that changes the pipeline:

• Final deliverable: image set, video, clips, audio, subtitles, dataset, social batch, product campaign, storyboard, style exploration.
• Source assets: product images, character references, first frames, video, audio, logo, transcript, brand guide.
• Runtime limits: quality target, cost sensitivity, number of variants, duration, aspect ratios, deadline.
• Continuity requirements: product identity, character face, scene layout, voice, color grade.
• Model preference: ask the user only when quality, speed, cost, or audio tradeoffs are not clear from the brief.

Core workflow

1. Write a short pipeline graph before running anything.

   input assets -> planner -> generation nodes -> utility nodes -> QA -> final outputs
   

2. Resolve endpoints for each role. Check known endpoint IDs first.

   genmedia models --endpoint_id openai/gpt-image-2 --json
   genmedia models --endpoint_id fal-ai/nano-banana-pro/edit --json
   genmedia models --endpoint_id bytedance/seedance-2.0/image-to-video --json
   genmedia models --endpoint_id xai/grok-imagine-video/image-to-video --json
   genmedia models --endpoint_id veed/fabric-1.0 --json
   

   Use text search only as fallback discovery for roles not covered by model-routing or the utility reference:

   genmedia models "image generation product photography" --json
   genmedia models "image editing reference preservation" --json
   genmedia models "image to video" --json
   genmedia models "subtitle video utility" --json
   genmedia docs "fal.ai workflow utility endpoints" --json
   

3. Inspect every endpoint before use.

   genmedia schema <endpoint_id> --json
   genmedia pricing <endpoint_id> --json
   

4. Upload local files once and reuse returned URLs.

   genmedia upload ./input.png --json
   genmedia upload ./voiceover.wav --json
   

5. Run each node with JSON output. Use async for slow generation.

   genmedia run <endpoint_id> --<field> "<value>" --json
   genmedia run <endpoint_id> --<field> "<value>" --async --json
   genmedia status <endpoint_id> <request_id> --download "./outputs/workflow/{request_id}_{index}.{ext}" --json
   

6. For downstream nodes, pass the media URL from the previous result when it is available. If you only have a local file path, upload it first.

7. Download final assets with templates that cannot collide.

   --download "./outputs/workflow/{request_id}_{index}.{ext}"
   

8. Return a compact manifest.

   {
     "goal" 
      
       
          
          
          
          
          
          
          
          
       
     
      
   
   

Pipeline rules

• Keep one node responsible for one clear transformation.
• Fan out independent generation, crop, upscale, subtitle, or variation nodes.
• Keep sequential chains only when node B needs node A output.
• For consistency, prefer reference/edit or image-to-video over independent text-only generations.
• For default creative model choices, follow model-routing unless the user names a model.
• Use utility endpoints for deterministic work: crop, resize, grid, composite, audio merge, subtitle, speed change, compression.
• Record endpoint, schema-relevant parameters, request ID, and output path for every node.
• If a 422 error occurs, read validation_errors, inspect schema again, then fix the exact field.

Quality gate

Before returning, verify:

• The pipeline graph matches the requested deliverable.
• No generation model was chosen from memory alone.
• All local source files were uploaded before use.
• Final files were saved through --download.
• Utility endpoints used exact schema fields.
• Continuity anchors were repeated where identity or product fidelity matters.
• Each node output is either accepted, retried, or marked with a defect.

If the workflow becomes too complex, stop expanding and ask the user to choose between faster iteration, higher fidelity, or broader variation.