Genmedia Workflow logo

Genmedia Workflow

Organization
fal-ai-community
genmedia-workflow

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.

Overview

Publisherfal-ai-community
Repositoryskills
Skill namegenmedia-workflow
Stars
255
Forks
35
Bundled files
4
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by fal-ai-community on GitHub. Read the source before you install it.

Installation

Install the Genmedia Workflow AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/fal-ai-community/skills/tree/main/skills/genmedia-workflow
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/fal-ai-community/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/genmedia-workflow .claude/skills/genmedia-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Genmedia Workflow in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Genmedia Workflow on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Genmedia Workflow is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

    text
    input assets -> planner -> generation nodes -> utility nodes -> QA -> final outputs
  2. Resolve endpoints for each role. Check known endpoint IDs first.

    bash
    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:

    bash
    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.

    bash
    genmedia schema <endpoint_id> --json
    genmedia pricing <endpoint_id> --json
  4. Upload local files once and reuse returned URLs.

    bash
    genmedia upload ./input.png --json
    genmedia upload ./voiceover.wav --json
  5. Run each node with JSON output. Use async for slow generation.

    bash
    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.

    bash
    --download "./outputs/workflow/{request_id}_{index}.{ext}"
  8. Return a compact manifest.

    json
    {
      "goal": "short deliverable description",
      "nodes": [
        {
          "id": "shot_01",
          "role": "image_to_video",
          "endpoint_id": "...",
          "request_id": "...",
          "input_urls": ["..."],
          "output_urls": ["..."],
          "downloaded_files": ["..."],
          "notes": "continuity or defect notes"
        }
      ],
      "final_files": ["..."]
    }

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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Genmedia Workflow AI skill do?

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.

Why use Genmedia Workflow on TypingMind?

Because you install it once and use it with any model. Genmedia Workflow is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Genmedia Workflow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fal-ai-community/skills/tree/main/skills/genmedia-workflow. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Genmedia Workflow?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Genmedia Workflow?

As many as you like. As long as a model supports skills, you can use Genmedia Workflow with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Genmedia Workflow AI skill free?

It is published on GitHub by fal-ai-community. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇