Install
$ agentstack add skill-pixelab-ch-higgsfield-skills-08-anime-action ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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
| | wan27 (primary) | wan26 (fallback) | |---|---|---| | Rationale | Flexible I2V; startimage attach point; wide aspect ratio support | When wan27 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](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](references/model-specs.md).
Prompt-building workflow
- Gather intent — Confirm with the user: anime genre (shonen, seinen, magical girl,
mecha, slice-of-life, etc.), target platform, aspect ratio, duration, and any specific visual effects or effects style.
- Select model — Apply the routing table above.
wan2_7by default.
- Build the prompt — Use the craft principles in the references below:
- 2-second hook technique from [references/hooks.md](references/hooks.md)
- Anime visual language, action choreography, style transfer, camera techniques from
[references/anime-craft.md](references/anime-craft.md)
- Worked example prompts by anime genre from [references/examples.md](references/examples.md)
- Present for review — Show the assembled prompt and all parameters to the user
for review and refinement before any upload or generation call.
Opt-in generation
Generation costs Higgsfield credits and requires explicit user confirmation. This skill never auto-generates.
Full step-by-step flow (confirmation gate, balance/cost surface, generate → poll → display): [../../shared/generation-flow.md](../../shared/generation-flow.md)
This skill's primary model: wan2_7
Media upload — MANDATORY (not conditional)
This skill always requires a source anime frame. The media branch is not conditional — it always runs before generation. Do not skip it.
Required sequence:
- Ask the user to provide the anime frame or illustration file (PNG, JPG, or WebP).
- Call
higgsfield:media_uploadwith the file → receives apending_id. - Call
higgsfield:media_confirmwith thepending_id→ receives aconfirmed_id. - Attach the
confirmed_idto theinput_filesarray before calling
higgsfield:generate_video:
- wan2_7 (primary): role =
start_image - wan2_6 (fallback): role =
image
// wan2_7 (primary)
input_files: [{ "id": "", "role": "start_image" }]
// wan2_6 (fallback)
input_files: [{ "id": "", "role": "image" }]
Never pass a pending_id directly to input_files. Never attempt generation without first completing the upload pair. wan2_6's image role is REQUIRED — a missing or unconfirmed image will cause the request to be rejected.
See [../../shared/generation-flow.md](../../shared/generation-flow.md) Step 2b for the atomic-pair detail and full input_files structure.
Tool signatures: [../../shared/mcp-tools.md](../../shared/mcp-tools.md)
Reference materials
| File | Contents | |---|---| | [references/model-specs.md](references/model-specs.md) | Verified parameter tables for wan27 (primary) and wan26 (fallback, image REQUIRED); routing rationale; re-verify directive | | [references/anime-craft.md](references/anime-craft.md) | Anime visual language, action choreography, style-transfer principles, camera techniques, lighting/color theory, genre identity guide, effects library | | [references/hooks.md](references/hooks.md) | 2-second hook framework with 12 anime hook techniques and genre selection guide | | [references/examples.md](references/examples.md) | Master prompt template plus 5 worked examples (shonen fight, magical girl, slice-of-life, mecha, emotional drama) |
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: pixelab-ch
- Source: pixelab-ch/higgsfield-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.