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/dsm5e/aso-trackernpx agentmods add skills/dsm5e/aso-tracker/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/dsm5e/aso-tracker/higgsfield-audio)<a href="https://agentmods.dev/skills/dsm5e/aso-tracker/higgsfield-audio"><img src="https://agentmods.dev/badge/skills/dsm5e/aso-tracker/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/dsm5e/aso-tracker/higgsfield-audio"><img src="https://agentmods.dev/badge/skills/dsm5e/aso-tracker/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 | $0.00108 | $0.03089 |
| Opus 5 | $0.00054 | $0.01545 |
| Sonnet 5 | $0.00022 | $0.00618 |
| Haiku 4.5 | $0.00011 | $0.00309 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Audio Prompting Guide
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 | ❌ | — | — | — | — | — |
"Native joint" means audio and video are generated simultaneously in one pass — not layered on after. This produces natural synchronization without post-production.
Models without native audio: add audio in post with Lipsync Studio or external tools.
The Four Audio Layers
Every audio-capable prompt should consider four layers. You don't need all four in every prompt, but knowing which to include gives the model clear direction.
1. Dialogue — What characters say
Put dialogue in quotes. Be explicit about who speaks, their tone, and language.
She says: "We need to leave. Now."
He whispers: "Not yet."
Best practices:
- Keep dialogue short — 1-2 sentences per character per shot
- Specify emotional tone: "says urgently", "whispers", "shouts across the room"
- For non-English: specify language and dialect →
She speaks in Cantonese: "走啦" - For Seedance 1.5 Pro: supports English, Chinese (incl. Sichuanese, Cantonese, Taiwanese Mandarin, Shanghainese), Japanese, Korean, Spanish, Indonesian
2. SFX — Specific sound events tied to action
Describe SFX at the point they happen. Tie them to visible actions.
The glass shatters on the floor — sharp crack, then settling tinkle.
Footsteps on wet concrete — splashing, rhythmic.
A door slams shut — heavy metal, echoing.
Best practices:
- One SFX description per action beat
- Use onomatopoeia sparingly — descriptive phrases work better than "BANG" or "CRASH"
- Tie timing to action: "as she sets the cup down" not "cup sound at 4 seconds"
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 · 324 lines · 108 tokens per session scan A 2ac9ef36e5a9
higgsfield-audio is a skill published in the GitHub repository dsm5e/aso-tracker (137 stars, last pushed 24d ago), licensed MIT. It adds 108 tokens to every session and 3,089 once invoked, about $0.0005 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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