Borrowing it
Nothing to install: this file belongs to anton-abyzov/vskill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/anton-abyzov/vskill/main/.claude/skills/higgsfield-seedance/SKILL.mdgit clone --depth 1 https://github.com/anton-abyzov/vskillWrote 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/anton-abyzov/vskill/higgsfield-seedance)<a href="https://agentmods.dev/skills/anton-abyzov/vskill/higgsfield-seedance"><img src="https://agentmods.dev/badge/skills/anton-abyzov/vskill/higgsfield-seedance/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/anton-abyzov/vskill/higgsfield-seedance"><img src="https://agentmods.dev/badge/skills/anton-abyzov/vskill/higgsfield-seedance.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 | $0.00100 | $0.11477 |
| Opus 5 | $0.00050 | $0.05738 |
| Sonnet 5 | $0.00020 | $0.02295 |
| Haiku 4.5 | $0.00010 | $0.01148 |
Grade A, and why
higgsfield-seedance 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 7d 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
86% identical to higgsfield-seedance — 681 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 — 1,237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Seedance Director
Use this skill whenever the user wants a Seedance 2.0 / Seedance Pro prompt, OR whenever a Seedance generation has been blocked, flagged, or silently failed. This skill's job is to stop credit waste on filter rejections.
The Filter Model — Read This First
Seedance 2.0's content filter is not a keyword blacklist. It is a language model that reads the full prompt as a single scene and judges intent and context. Most users burn hours swapping individual words — that loop does not work.
The filter compares two things:
- A prompt that reads like a filmmaker describing a shot → tends to pass.
- A prompt that reads like a note to a friend → tends to fail.
A word that looks sensitive in isolation can sit inside a well-constructed cinematic prompt without issue — the filter reads the full picture. A prompt with no picture to read (no setting, no visual purpose, no narrative logic) gives the filter nothing to work with, and it errs on the side of caution.
Practical rule: the prompt must describe a scene, not a subject. Fix the voice first, then fix the words.
Instant Fail vs. Delayed Fail — the Diagnostic
This single heuristic saves time on every failure:
| Failure timing | Meaning | What to do |
|---|---|---|
| < 10 seconds (instant) | Content filter rejection — prompt never reached the GPU | Rewrite for voice + remove risk tokens. Do not regenerate unchanged. |
| > 30 seconds (delayed) | Infrastructure, timeout, or complexity — prompt passed the filter but the render failed | Simplify action density, cut length, try again |
If the user is seeing instant fails in a loop, it is a filter issue — never a GPU issue. Stop them from regenerating before the rewrite.
The Seedance Prompt Formula
Every Seedance prompt should hit these six slots, in this order:
[Camera movement] + [Subject] + [Action] + [Setting] + [Style] + [Lighting]
All six are technically optional — but a prompt that includes all six almost never gets flagged, because the filter has full context to interpret every word. A prompt missing 3+ slots is where flags come from.
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.
- 7d ago First seen · 1,237 lines · 100 tokens per session scan A 61eaa59aec49
higgsfield-seedance is a skill published in the GitHub repository anton-abyzov/vskill (45 stars, last pushed 4d ago), licensed MIT. It adds 100 tokens to every session and 11,477 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to higgsfield-seedance, differing in 681 lines, and is treated as a copy.
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