Video teaser
Ready-to-install agent skills, each wrapping a nanoodle visual AI workflow — poster, photo restyle, jingle, narrated poem, video teaser
npx -y skills add nanoodlecom/noodle-skills --skill video-teaserAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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What its author says it does
Copied from the file, not written here
Turn a one-liner into a short video clip — an LLM expands the line into a cinematic shot description, then a text-to-video model renders a 5-second teaser. Use when the user wants a short video, teaser, clip, or animated shot from a sentence.
SKILL.md
2.5 KB, as published. Nobody here has run it
Video teaser
Runs the bundled nanoodle workflow workflows/video-teaser.noodle-graph.json against the
NanoGPT API: a one-liner (Tagline) feeds an LLM that writes a single cinematic shot
description, which feeds a text-to-video model that renders a 5-second 480p clip
(Teaser). Requires Node.js >= 20 and the nanoodle npm package (npx nanoodle fetches
it).
API key
The run needs a NanoGPT API key. Prefer NANOGPT_API_KEY already in the environment.
Otherwise pass --env-file <path-to-.env> (this CLI: --env-file overrides ambient env).
Never print the key.
Run
From this skill's directory (or prefix paths if running from elsewhere). Replace the
Tagline value with the user's line:
npx nanoodle run workflows/video-teaser.noodle-graph.json \
--input "Tagline=a slow cinematic drone shot over a misty mountain valley at sunrise" \
--out ./teaser-out
Add --env-file .env only when the key is not already exported. Add --json for a
structured result (paths, costUsd, remainingBalance). Video generation typically takes a
few minutes — don't kill the run early.
Optional overrides (each raises cost — see Cost below):
--input "System prompt=<custom shot-writer instructions>"
--set "n3.resolution=720p" # sharper (about $0.08/run) — 1080p about $0.12
--set "n3.duration=10" # longer clip (roughly doubles the video cost)
--set "n3.aspect=9:16" # portrait
Inspect the interface anytime with:
npx nanoodle inspect workflows/video-teaser.noodle-graph.json
Inputs
| Key | Required | What to pass |
|---|---|---|
Tagline | yes | The one-line concept for the clip |
System prompt | no | Custom instructions for the shot-writing LLM |
Outputs
- Media is saved under
--outasTeaser.<ext>— extension follows the video MIME (usuallymp4). Use the path the CLI prints on theTeaser:line; do not hard-code the extension. - With
--json, the path is inoutputs.Teaser.
Cost
Each run costs about $0.06 in NanoGPT credit at the default 5 seconds / 480p
(ltx-2-19b bills per second by resolution; the LLM step is a fraction of a cent).
Higher resolution or 10-second clips cost proportionally more. Runs spend real credit —
tell the user before running repeatedly.
Gives 0 of the 12 instructions most video audio skills give
Counted across 621 of the 795 authors here whose files we hold, read 2026-08-06
- read individual rule files for detailed explanationsin 21 of 621, across 9 files
- Use WAV PCM 16kHz mono audio formatin 13 of 621, across 4 files
- render final videoin 13 of 621, across 6 files
- use this skill when dealing with Remotion codein 11 of 621, across 4 files
- save generated audio to a WAV filein 11 of 621, across 4 files
- handle conversion errors gracefullyin 10 of 621, across 6 files
- add captions to videos alwaysin 10 of 621, across 4 files
- generate music from text descriptions using MusicGenin 9 of 621, across 2 files
- do not skip pipeline layersin 9 of 621, across 3 files
- do not make one tool do everythingin 9 of 621, across 3 files
- never ask the user to paste their full API keyin 9 of 621, across 3 files
- use azure document intelligence for complex pdfsin 9 of 621, across 4 files
Said here and by no other author read
- Use the bundled nanoodle workflow file
- Replace the Tagline value with the user's line
- Write output to a designated directory
- Prefer NANOGPT_API_KEY from the environment
- Pass an env file if the key is not exported
- Use the Teaser path printed by the CLI
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.