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 1370998960-del/https-github.com-Emily2040-seedance-2.0 --skill seedance-vocab-engit clone --depth 1 https://github.com/1370998960-del/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/1370998960-del/https-github.com-emily2040-seedance-2.0/seedance-vocab-en)<a href="https://agentmods.dev/skills/1370998960-del/https-github.com-emily2040-seedance-2.0/seedance-vocab-en"><img src="https://agentmods.dev/badge/skills/1370998960-del/https-github.com-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/1370998960-del/https-github.com-emily2040-seedance-2.0/seedance-vocab-en"><img src="https://agentmods.dev/badge/skills/1370998960-del/https-github.com-emily2040-seedance-2.0/seedance-vocab-en.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00891 |
| Opus 5 | $0.00030 | $0.00445 |
| Sonnet 5 | $0.00012 | $0.00178 |
| Haiku 4.5 | $0.00006 | $0.00089 |
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 10d 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.
This is a copy
88% identical to seedance-vocab-en — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
seedance-vocab-en
English is the default prompting language and fails in two ways at once: slop (empty evaluation words that add tokens and no signal) and false positives (vague threat-adjacent wording that trips the heaviest moderation surface). The cure for both is the same: concrete production English. Preserve reference tags exactly: [Image1], [Video1], [Audio1] must never be reworded.
Intent
English is where most users think, and where most prompts quietly rot. The soul of this vocabulary is precision as kindness: give people exact words so their excitement survives contact with the model, and so honest prompts stop being mistaken for dangerous ones.
Usage Rule
If a camera, microphone, light meter, or stopwatch cannot detect it, rewrite it. Every sentence should name something visible, audible, or measurable: subject, visible action, camera, light source, sound, constraint.
| 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 |
De-Slop Pass
Strip quality adjectives before adding anything: cinematic, epic, stunning, masterpiece, 8K, ultra-realistic, award-winning, hyper-detailed all delete or convert to one observable detail each. A prompt that earns "epic" names the crowd size, the lens distance, or the structure height instead of the word.
Filter-Aware Wording
English homonyms read as threats to filters: shoot the scene, kill the lights, gun it, dead silence, blow up the image. Use the production synonym (film the take, cut the lights to black, accelerate hard, held silence, enlarge to full frame). This is clarity for safe prompts only — never evasion. Anything genuinely risky (minors, real-person likeness, sexual or graphic content) routes to [skill:seedance-filter] for its boundary rule, not to a rewording.
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.
- 10d ago First seen · 59 lines · 61 tokens per session scan A 498e83a6aef1
seedance-vocab-en is a skill published in the GitHub repository 1370998960-del/https-github.com-Emily2040-seedance-2.0 (235 stars, last pushed 2mo ago), licensed MIT. It adds 61 tokens to every session and 891 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to seedance-vocab-en, differing in 26 lines, and is treated as a copy.
Other skills, from other repositories
seedance-vocab-en
This skill should be used when an English Seedance 2.0 prompt needs clearer production wording, less generic prose, or precise vocabulary for camera, lighting, motion, VFX, audio, and constraints. Route blocked prompts through seedance-filter for context and boundary review.
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-zh
This skill should be used when the user asks for Chinese Seedance 2.0 prompt wording, Mandarin cinematic vocabulary, Chinese prompt compression, or translation of camera, lighting, action, VFX, audio, and production terms into Chinese.
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.