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SKILL verified MIT Self-run

Higgsfield Anime Action

skill-pixelab-ch-higgsfield-skills-08-anime-action · by pixelab-ch

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Install

$ agentstack add skill-pixelab-ch-higgsfield-skills-08-anime-action

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No 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.

View the full security report →

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Reliability & compatibility

Security review passed
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4mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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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_uploadhiggsfield: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

  1. 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.

  1. Select model — Apply the routing table above. wan2_7 by default.
  1. 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)
  1. 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:

  1. Ask the user to provide the anime frame or illustration file (PNG, JPG, or WebP).
  2. Call higgsfield:media_upload with the file → receives a pending_id.
  3. Call higgsfield:media_confirm with the pending_id → receives a confirmed_id.
  4. Attach the confirmed_id to the input_files array 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.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.