Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skillnpx agentmods add skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-audioWrote 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/osidemedia/higgsfield-ai-prompt-skill/higgsfield-audio)<a href="https://agentmods.dev/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-audio"><img src="https://agentmods.dev/badge/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-audio/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/osidemedia/higgsfield-ai-prompt-skill/higgsfield-audio"><img src="https://agentmods.dev/badge/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-audio.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 | $0.00144 | $0.09267 |
| Opus 5 | $0.00072 | $0.04633 |
| Sonnet 5 | $0.00029 | $0.01853 |
| Haiku 4.5 | $0.00014 | $0.00927 |
Grade A, and why
higgsfield-audio 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 754 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Audio Prompting Guide
QUICK FACTS
Routing aids — read the linked sections for the full rules.
- Native-joint audio models: Kling 3.0, Seedance 2.0 / 1.5 Pro, Veo 3/3.1, Grok — all others add audio in post →
- Four layers to consider per prompt: Dialogue / SFX / Ambient / BGM →
- Lip-sync is the most failure-prone feature: 3–8s clips, MCU framing, one speaking face, locked camera, no head-motion tokens; per-language sync-word budgets are FIELD-reported →
- Seedance 2.0
@Audio1is a conditioning INPUT — beat sync, the[AUDIO: Xs]script block, and the first-15s extraction trap → - Scope an audio reference like an image one: name the property that rides, the property that must NOT, and where the excluded one comes from instead →
- Multi-clip assembly: one master track · cuts land on musical punctuation, never inside a sung vowel (ECU mouth-match is the one exception) · unified grain + LUT masks batch color drift →
- Cinema Studio 3.0 native joint audio (SCELA): describe audio as a separate section; specific foley beats generic moods →
- Seed Audio 1.0 (
seed_audio, standalone) = whole-scene audio in ONE pass — multi-speaker dialogue + music + SFX + ambience mixed → - Standalone Audio catalog (2026-08-01 snapshot):
seed_audio,qwen_audio_tts(NEW — Qwen 3.0 TTS Flash, expressive instructions + cloned voices),text2speech_v2(5 engines incl. cozy_voice), plus 3 game-pipeline-only tools — distinct from in-video joint audio →
Which Models Support Audio?
| Model | Audio type | Dialogue | SFX | Ambient | BGM | Lip-sync |
|---|---|---|---|---|---|---|
| Kling 3.0 / Omni | Native joint | ✅ | ✅ | ✅ | ✅ | ✅ Multi-language |
| Seedance 2.0 | Native joint | ✅ | ✅ | ✅ | ✅ | ✅ Multi-language |
| Seedance 1.5 Pro | Native joint | ✅ | ✅ | ✅ | ✅ | ✅ Best lip-sync |
| Veo 3 / 3.1 | Native joint | ✅ | ✅ | ✅ | ✅ | ✅ English best |
| Grok Imagine Video | Native joint | ✅ | ✅ | ✅ | ✅ | ✅ |
| All other models | ❌ | — | — | — | — | — |
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.
- 13d ago First seen · 754 lines · 144 tokens per session scan A 54c79f1e33d5
higgsfield-audio is a skill published in the GitHub repository OSideMedia/higgsfield-ai-prompt-skill (531 stars, last pushed 20d ago), licensed MIT. It adds 144 tokens to every session and 9,267 once invoked, about $0.0007 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.
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