fal-ai-community/skills

storytelling

Build multi-shot narrative image, video, and audio workflows with genmedia. Use this for storyboards, shot lists, multi-prompt video, first-frame to last-frame pipelines, social stories, brand films, and sequence continuity.

First seen May 1, 2026

Installation

$ npx skills add fal-ai-community/skills --skill storytelling

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 237
License MIT
Default branch main
Open issues 2
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,658 B
  • docs SUMMARY.md 244 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 270 installs

SKILL.md

Storytelling with genmedia

Use this skill when the user wants a sequence, not a single asset. Load references as needed:

  • references/shot-planning.md
  • references/workflows.md
  • references/examples.md

Load model-routing alongside this skill for default endpoint choices.

The goal is to produce clear story beats and executable genmedia runs. Avoid generic inspiration copy, fake dialogue, and em dashes.

Inputs to collect

Ask only when missing information affects execution.

  • Format: ad, short film, music video, documentary, tutorial, social story.
  • Duration and aspect ratio.
  • Number of shots or allowed range.
  • Main subject, character, product, or location.
  • Continuity anchors: character, product, wardrobe, environment, color.
  • Source media: first frame, reference image, product shot, audio track.
  • Audio needs: narration, music, sound design, transcript, no audio.
  • Preferred model or model family, if the user wants to decide quality, cost,

speed, audio, or multi-shot tradeoffs.

Genmedia workflow

  1. Start from routed endpoint IDs.

``bash genmedia models --endpointid bytedance/seedance-2.0/text-to-video --json genmedia models --endpointid bytedance/seedance-2.0/image-to-video --json genmedia models --endpointid bytedance/seedance-2.0/reference-to-video --json genmedia models --endpointid fal-ai/kling-video/v3/pro/text-to-video --json genmedia models --endpointid alibaba/happy-horse/text-to-video --json genmedia models --endpointid veed/fabric-1.0 --json ``

Use text search only as fallback discovery for an unsupported sequence control:

``bash genmedia models "first frame last frame video generation" --json genmedia docs "multi shot video generation" --json ``

  1. Inspect schema before planning exact payloads.

``bash genmedia schema <endpointid> --json genmedia pricing <endpointid> --json ``

  1. Upload references.

``bash genmedia upload ./first-frame.png --json genmedia upload ./character.png --json genmedia upload ./product.png --json genmedia upload ./voiceover.wav --json ``

  1. Choose the sequence route.

- Highest quality video: start with Seedance 2.0 endpoints from model-routing. - Native multi-prompt: use if schema has shot arrays, prompt lists, or timeline fields. - First/last frame: use for controlled transitions between key frames. - Image-to-video per shot: use for maximum continuity from approved stills. - Manual per-shot generation: use when the model only supports one prompt. - Audio-first: generate or upload audio, then plan visual shot lengths. - Lip-sync or talking avatar: use Fabric 1.0 or Creatify Aurora from model-routing.

  1. Run long jobs async and download every result with a unique template.

```bash genmedia run <endpoint_id> \ --prompt "<shot or sequence prompt>" \ --async \ --json

genmedia status <endpointid> <requestid> \ --download "./outputs/story/{requestid}{index}.{ext}" \ --json ```

  1. Return a shot table with endpoint, request id, prompt summary, local path,

and any continuity issues. Genmedia downloads clips; it does not replace a timeline editor unless the chosen model returns a complete stitched video.

Shot planning

Plan every sequence as beats first:

  1. Hook: immediate visual reason to keep watching.
  2. Setup: who, what, where, and why it matters.
  3. Development: movement, discovery, proof, or escalation.
  4. Turn: reveal, transformation, result, or emotional change.
  5. Close: final image, product memory, CTA-safe frame, or unresolved mood.

For each shot, write:

  • Shot number and duration.
  • Story purpose.
  • Visual prompt.
  • Continuity anchor.
  • Input reference, if any.
  • Genmedia endpoint.
  • Expected output path.

Prompt build order

Use this structure for each shot:

SHOT [number], [duration]:
[story purpose]. [subject and action]. [location and time]. [camera framing].
[camera movement]. [lighting and color]. [continuity anchor]. [transition or
relationship to previous shot].

Keep one shot to one clear action unless the selected model supports multi-shot or timeline prompting.

Model routing

  • Highest quality video: bytedance/seedance-2.0/text-to-video,

bytedance/seedance-2.0/image-to-video, or bytedance/seedance-2.0/reference-to-video.

  • Fast or lower-cost video: xai/grok-imagine-video/text-to-video or

xai/grok-imagine-video/image-to-video.

  • Multi-shot sequence: Seedance 2.0 first, then

fal-ai/kling-video/v3/pro/text-to-video, then fal-ai/kling-video/v3/pro/image-to-video, then alibaba/happy-horse/text-to-video or alibaba/happy-horse/image-to-video.

  • Text-heavy keyframes, boards, UI frames, posters, or infographics:

openai/gpt-image-2 at quality=high.

  • Talking avatar, native audio, or lip-sync:

veed/fabric-1.0, veed/fabric-1.0/text, or fal-ai/creatify/aurora.

Quality bar

Before returning:

  • Shot order has a clear narrative function.
  • The first shot is strong enough for the platform.
  • Continuity anchors are repeated without bloating every prompt.
  • Camera motion is varied but not random.
  • Durations add up to the requested runtime.
  • Async request IDs and downloaded files are recorded.
  • The model's actual schema, not assumptions, drove the final command.