seedance-2.0 is an agent-driven production pipeline for creating AI films from text, images, videos, and references, including audio and platform-specific workflows. Filmmakers and creators use it to plan scenes and generate coherent prompts for Seedance-related tools, while the catalogue contains skills from that workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Emily2040/seedance-2.0 --skill seedance-vocab-engit clone --depth 1 https://github.com/Emily2040/seedance-2.0Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/emily2040/seedance-2.0/seedance-vocab-en)<a href="https://agentmods.dev/skills/emily2040/seedance-2.0/seedance-vocab-en"><img src="https://agentmods.dev/badge/skills/emily2040/seedance-2.0/seedance-vocab-en/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/emily2040/seedance-2.0/seedance-vocab-en"><img src="https://agentmods.dev/badge/skills/emily2040/seedance-2.0/seedance-vocab-en.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.01065 |
| Opus 5 | $0.00030 | $0.00532 |
| Sonnet 5 | $0.00012 | $0.00213 |
| Haiku 4.5 | $0.00006 | $0.00106 |
Grade A, and why
seedance-vocab-en scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
3 near-identical copies found in the catalogue:
- seedance-vocab-en — 88% identical, 26 lines differ
- seedance-vocab-en — 86% identical, 24 lines differ
- seedance-vocab-en — 86% identical, 24 lines differ
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
seedance-vocab-en
Before producing prompt text, a prompt-ready block, a rewrite, an example, or a compiled clip, load the Director's Read, classify the brief, and complete its canonical narrative or non-narrative record. Translate that record into visible or audible carriers and keep its internal labels out of final generation prose.
Use this skill when the user chooses English prompt wording. Concrete production language can make the intended scene easier to review; it is not a demonstrated cure for moderation errors. This repository has no matched evidence that English receives heavier moderation than other languages. Preserve actual reference tags exactly; their spelling is independent of the prompt language.
Before adapting a reference example below, load Using Reference Examples. Bind its placeholders to real assets by the requested role, then preserve the actual token, including its script, case, spacing and punctuation. A written example token does not attach a file.
Intent
Help the user express the intended action, camera, light and sound clearly. Preserve their chosen language, exact dialogue, reference bindings and creative constraints. Separate a wording clarification from a proposal to change what happens in the scene.
Usage Rule
Use visible or audible detail when a phrase leaves a relevant production choice unclear. Keep useful genre, style and mood labels. The examples below are optional vocabulary, not required camera moves, lighting setups or limits on scene complexity.
| Function | English wording |
|---|---|
| Camera | slow push-in, locked medium shot, stable lateral tracking, pull back to reveal, macro close-up |
| Lighting | soft backlight, warm practical light from the left, cool moonlight rim, wet asphalt reflecting neon |
| Motion | a slow head turn that stops, droplets merge and slide down, fabric settles after the gesture |
| Audio | quiet room tone, one clear spoken line in quotes, no music until after the line |
| Constraints | keep the logo, label, and shape unchanged, one action, one camera move, nothing else moves |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed · +2 lines 7abdd2b47a87
- 13d ago First seen · 61 lines · 61 tokens per session scan A 9cd5c100bea9
seedance-vocab-en is a skill published in the GitHub repository Emily2040/seedance-2.0 (7,279 stars, last pushed 4d ago), licensed MIT. It adds 61 tokens to every session and 1,065 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
seedance-vocab-en
This skill should be used when an English Seedance 2.0 prompt is slop-heavy, generic, padded with empty quality words, tripping false-positive filters, or needs precise English production vocabulary for camera, lighting, motion, VFX, audio, and constraints.
seedance-vocab-en
This skill should be used when an English Seedance 2.0 prompt is slop-heavy, generic, padded with empty quality words, tripping false-positive filters, or needs precise English production vocabulary for camera, lighting, motion, VFX, audio, and constraints.
seedance-antislop
This skill should be used when a Seedance 2.0 prompt contains generic AI filler, hollow superlatives, vague cinematic language, bloated adjectives, weak verbs, or needs sharper production-specific wording.
seedance-vocab-en
This skill should be used when an English Seedance 2.0 prompt is slop-heavy, generic, padded with empty quality words, tripping false-positive filters, or needs precise English production vocabulary for camera, lighting, motion, VFX, audio, and constraints.
seedance-prompt
This skill should be used when the user asks to write, improve, translate, compress, or debug a Seedance 2.0 video prompt; mentions T2V, I2V, V2V, R2V, camera direction, prompt quality, or provides reference assets for a production-ready prompt.
seedance-examples-ja
This skill should be used when the user asks for Japanese Seedance 2.0 examples, Japanese prompt patterns, example rewrites, or safe versions of working Japanese video-generation prompts.