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 dsm5e/aso-tracker --skill higgsfield-modelsgit clone --depth 1 https://github.com/dsm5e/aso-trackerWrote 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-models)<a href="https://agentmods.dev/skills/dsm5e/aso-tracker/higgsfield-models"><img src="https://agentmods.dev/badge/skills/dsm5e/aso-tracker/higgsfield-models/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-models"><img src="https://agentmods.dev/badge/skills/dsm5e/aso-tracker/higgsfield-models.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 | $0.00062 | $0.04676 |
| Opus 5 | $0.00031 | $0.02338 |
| Sonnet 5 | $0.00012 | $0.00935 |
| Haiku 4.5 | $0.00006 | $0.00468 |
Grade A, and why
higgsfield-models 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 9d 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
92% identical to higgsfield-models — 32 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Model Selection Guide
Choosing the right model is the single biggest factor in output quality after the prompt.
This file handles most selection questions. For deep per-model documentation (prompting
specifics, parameters, edge cases, API details) → read MODELS-DEEP-REFERENCE.md.
Quick Decision Flowchart
Fast lookup — for detailed comparisons see the full tables below.
| Need | Recommended Model | Tier |
|---|---|---|
| Top-tier cinematic video + audio | Kling 3.0 | Premium |
| Epic scale / spectacle | Sora 2 | Premium |
| Nature / landscapes + ref images | Veo 3.1 | Premium |
| Artistic / stylized video | Wan 2.6 | Mid |
| Fast video iteration | Seedance 2.0 Pro | Mid |
| VFX / fluid motion | Minimax Hailuo 2.3 | Mid |
| Budget-friendly video | Kling 2.5 Turbo / Higgsfield DoP Lite | Free–Low |
| Fashion / aesthetic images | Soul 2.0 | Free |
| Photorealistic sharp images | Nano Banana Pro | Low |
| AI actor generation | Soul Cast | Low |
| Native 4K images | Kling Image 3.0 | Mid |
| Photo style transformation | Photodump (29 presets) | Low |
Pricing tiers: Free (Soul 2.0, DoP Lite) · Low (0.1–2 credits) · Mid (2–10 credits) · Premium (10+ credits). See the Credit Cost Reference below for exact per-model costs.
Video Models — Comparison
| Model | Realism | Character | Motion | Style | Duration | Audio | Best for |
|---|---|---|---|---|---|---|---|
| Kling 3.0 | ★★★★★ | ★★★★★ | ★★★★★ | ★★★★☆ | 3–15s | ✅ | Cinematic, long, audio, multi-shot |
| Kling 3.0 Omni | ★★★★★ | ★★★★★ | ★★★★★ | ★★★★☆ | 3–15s | ✅ | Video clone, storyboard control |
| Kling 3.0 Omni Edit | ★★★★★ | ★★★★★ | — | ★★★★☆ | 3–10s | ✅ | Edit footage at 3.0 quality |
| Kling O1 Video (legacy) | ★★★★★ | ★★★★★ | ★★★★☆ | ★★★☆☆ | 5–10s | ❌ | Multi-ref (7), start/end frame |
| Kling O1 Video Edit (legacy) | ★★★★☆ | ★★★★★ | — | ★★★★★ | 3–10s | ❌ | Relight, restyle, swap, remove |
| Kling 3.0 Motion Control | ★★★★★ | ★★★★☆ | ★★★★★ | ★★★☆☆ | 3–30s | Optional | Motion transfer from reference video |
| Kling 2.6 (legacy) | ★★★★★ | ★★★★★ | ★★★★☆ | ★★★☆☆ | 5–10s | ❌ | Character drama, realism (no audio) |
| Kling 2.5 Turbo | ★★★★☆ | ★★★★☆ | ★★★★☆ | ★★★☆☆ | 5–10s | ❌ | Fast Kling iteration |
| Sora 2 | ★★★★☆ | ★★★☆☆ | ★★★★★ | ★★★★☆ | — | ❌ | Epic scale, physics, action |
| Wan 2.7 | ★★★★★ | ★★★★☆ | ★★★★★ | ★★★★★ | 2–15s | ✅ | 60fps, T2V/I2V/R2V/edit, first+last frame |
| Wan 2.6 | ★★★★☆ | ★★★☆☆ | ★★★★☆ | ★★★★★ | 5–15s | ❌ | Artistic, stylized, improved physics |
| Wan 2.5 | ★★★★☆ | ★★★☆☆ | ★★★★☆ | ★★★★★ | 5–10s | ✅ | Native audio, artistic, fantasy |
| Seedance 2.0 | ★★★★★ | ★★★★★ | ★★★★★ | ★★★★☆ | 10s | ✅ | 12-asset multimodal, complex motion |
| Seedance 1.5 Pro | ★★★★☆ | ★★★★☆ | ★★★★☆ | ★★★★☆ | 10s | ✅ | Best lip-sync, multilingual audio |
| Seedance Pro | ★★★☆☆ | ★★★☆☆ | ★★★☆☆ | ★★★☆☆ | 10s | ❌ | Fast iteration, no audio needed |
| Veo 3.1 | ★★★★★ | ★★★★☆ | ★★★★☆ | ★★★★☆ | 4–8s | ✅ | Ref images, first/last frame, 4K |
| Veo 3.1 Lite | ★★★★☆ | ★★★★☆ | ★★★★☆ | ★★★★☆ | 4–8s | ✅ | Budget 3.1 quality, 1080p, I2V, volume |
| Veo 3 | ★★★★☆ | ★★★☆☆ | ★★★★☆ | ★★★☆☆ | 4–8s | ✅ | Nature, environment, stable model |
| Grok Imagine Video | ★★★★☆ | ★★★☆☆ | ★★★★☆ | ★★★★☆ | 1–15s | ✅ | Video editing, animate images |
| Minimax Hailuo 2.3 | ★★★★★ | ★★★★☆ | ★★★★★ | ★★★★☆ | 6–10s | ❌ | VFX, fluid motion, anime, physics |
| Minimax Hailuo 02 | ★★★★☆ | ★★★☆☆ | ★★★★★ | ★★★☆☆ | 6–10s | ❌ | Dance, sports, fluid motion |
| Higgsfield DoP (Lite/Standard/Turbo) | ★★★☆☆ | ★★★☆☆ | ★★★★☆ | ★★★☆☆ | 3–5s | ❌ | I2V specialist, 50+ presets, optical physics |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 270 lines · 62 tokens per session scan A 2fe1bddbf486
higgsfield-models is a skill published in the GitHub repository dsm5e/aso-tracker (136 stars, last pushed 23d ago), licensed MIT. It adds 62 tokens to every session and 4,676 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to higgsfield-models, differing in 32 lines, and is treated as a copy.
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