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 pixelab-ch/higgsfield-skills --skill 08-anime-actiongit clone --depth 1 https://github.com/pixelab-ch/higgsfield-skillsWrote 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/pixelab-ch/higgsfield-skills/08-anime-action)<a href="https://agentmods.dev/skills/pixelab-ch/higgsfield-skills/08-anime-action"><img src="https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/08-anime-action/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/pixelab-ch/higgsfield-skills/08-anime-action"><img src="https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/08-anime-action.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 | $0.00160 | $0.01725 |
| Opus 5.5 | $0.00064 | $0.00690 |
| Sonnet 5.5 | $0.00032 | $0.00345 |
| Haiku 4.5 | $0.00016 | $0.00172 |
Grade A, and why
higgsfield-anime-action 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 1mo 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Anime-Action Skill
What this skill does
Generates anime-style video from a user-supplied anime frame or illustration using Higgsfield. The skill applies the anime visual language — cel shading, limited animation, impact frames, speed lines, color psychology — to bring the source image into motion.
A source anime frame is always required. This skill is a mandatory image-to-video (I2V)
skill — it animates a user-supplied image and cannot run without one. Before any generation
call can happen, the user must provide the anime frame and the
higgsfield:media_upload → higgsfield:media_confirm flow must complete successfully.
Model routing
Primary and fallback video models
| wan2_7 (primary) | wan2_6 (fallback) | |
|---|---|---|
| Rationale | Flexible I2V; start_image attach point; wide aspect ratio support | When wan2_7 unavailable; discrete durations only |
| Resolution | 720p, 1080p |
720p, 1080p |
| Aspect ratios | 16:9, 9:16, 1:1, 4:3, 3:4 |
16:9, 9:16, 1:1 only — no 4:3 or 3:4 |
| Duration | 2–15 s (continuous range) | 5, 10, 15 s — discrete set only |
| Image role | start_image |
image x1 REQUIRED |
Routing rule: Use wan2_7 by default. Fall back to wan2_6 when wan2_7 is unavailable.
If falling back, inform the user that: (1) duration becomes discrete [5, 10, 15] only —
no 2, 3, 4, 6, 7, 8, 9 etc., (2) 4:3 and 3:4 aspect ratios are not available, and
(3) the image role changes from start_image to image. Never switch models silently.
MODEL-06 directive: If a parameter is rejected at generation time, call
higgsfield:models_explore with the target model name. Full parameter tables:
references/model-specs.md.
Per-platform aspect ratio and duration
Quick rule: 9:16 for TikTok / Reels / Shorts, 16:9 for YouTube, 1:1 for Instagram
feed, 3:4 for portrait/manga format (wan2_7 only). Full per-platform table:
references/model-specs.md.
What ships with it
4 files 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.
- 1mo ago First seen · 142 lines · 160 tokens per session scan A 4240c70902ee
higgsfield-anime-action is a skill published in the GitHub repository pixelab-ch/higgsfield-skills (10 stars, last pushed 5mo ago), licensed MIT. It adds 160 tokens to every session and 1,725 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
create-short
Create a short-form vertical video (TikTok, Instagram Reels, YouTube Shorts). Optimized 9:16 pipeline with a live Studio preview, auto-captions, hook-first structure, and background music mood selection; renders to MP4 only when you ask.
create-video
Full video production pipeline — from a text prompt to a live Studio preview with voiceover, music, sound effects, stock footage, and motion graphics, rendered to MP4 when you ask. The flagship command of Remotion Superpowers.
review-video
Review a Remotion video with AI vision. Starts with a cheap local check of rendered still frames, then has TwelveLabs watch the full render and score it against a JSON rubric (pacing, composition, text legibility, audio sync and more) with timestamped fixes, applies the fixes and re-reviews. The feedback loop that…
add-captions
Add TikTok-style, karaoke, YouTube or minimal captions to your Remotion video. Gets word-level captions through the official remotion-captions flow (whisper-webgpu, or ElevenLabs Scribe via @remotion/elevenlabs when there's no GPU), or imports the user's SRT with parseSrt, places one official caption element per clip…
analyze-footage
Analyze existing video files with TwelveLabs AI. Get a timestamped scene map of your footage, ask questions about it, find specific moments across a library, and get the best clips with timestamps for Remotion.
generate-clip
Generate AI video clips for your Remotion project. Create unique footage from text descriptions or animate still images into video — no stock footage needed.