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Higgsfield media

Skill nuwansamaranayake/AiGNITEClaudeAssets/higgsfield-media

Nine Claude Code skills that turn one developer into a mobile app studio. Built for AiGNITE Consulting's MCP-first product portfolio.

Install
npx -y skills add nuwansamaranayake/AiGNITEClaudeAssets --skill higgsfield-media

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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What its author says it does

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Generate professional images and videos using the Higgsfield MCP server. Supports 30 plus models including Soul V2, Nano Banana Pro, GPT Image 2, Flux 2 Pro, Seedream 4.5, Seedream 5.0 Lite, Kling 3.0, Seedance 2.0, Veo 3.1, and Sora 2. Use this skill whenever the user wants to generate an image, generate a video, create an ad creative, make a product photo, make a UGC video, build a social pack, create a LinkedIn cover, design a hero image, build a newsletter header, design a blog hero, produce architecture-diagram backdrops, or generate any visual asset where Higgsfield is appropriate. Triggers also fire on phrases like use Higgsfield, with Kling, with Veo, with Sora, with Seedance, Nano Banana, Soul V2, Soul Character, Flux 2, GPT Image, Marketing Studio, ad pack, social pack, 5-second clip, 15-second video, cinematic ad, product hero shot, lifestyle photo, reel, TikTok video, YouTube short, AI image, AI video, Instagram reel. Use even if the user does not name Higgsfield. Requires an active Higgsfield subscription and the Higgsfield MCP server connected via claude mcp add --transport http --scope user higgsfield https://mcp.higgsfield.ai/mcp.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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higgsfield-media

Purpose

Turn a creative brief into a finished image or video asset (or a coordinated set of assets) using the right Higgsfield model for the job, at the right credit cost, with the output saved to disk and a manifest written for downstream skills to consume.

Preflight check

Run before every brief.

  1. Verify Higgsfield MCP is connected. Run scripts/check-mcp.ps1. If the script exits non-zero, print the one-line install command and stop:
claude mcp add --transport http --scope user higgsfield https://mcp.higgsfield.ai/mcp
  1. Verify credit balance. Run scripts/check-balance.ps1. Block if balance is below 50 credits and the planned batch will overrun.

Behavior: seven phases

The skill runs in seven phases. Skip a phase only when the user says so.

Phase 1: Preflight

MCP connected. Balance fetched. Credit ledger read for the current month.

Phase 2: Brief intake

Read the user's request. Extract:

  • Asset type (image, video, multi-asset pack)
  • Quantity (single, batch of N, full pack)
  • Aspect ratio (1:1, 16:9, 9:16, 4:5)
  • Output usage (LinkedIn, Instagram, blog hero, ad, internal slide)
  • Subject (product, person, scene, abstract)
  • Style cues (cinematic, flat lay, lifestyle, editorial, illustration)
  • Text requirement (any copy that must render legibly)
  • Character consistency requirement
  • Budget cap if specified

Ask at most three pointed questions for missing fields. Default to sensible choices when in doubt.

Phase 3: Model selection

Apply the decision matrix in references/model-selection.md. Prefer unlimited models for iteration. Reserve paid credits for the final render. Print the selected model and the cost estimate before generating.

Phase 4: Cost confirmation

Compute projected credits for the full batch. Print one line:

model=<slug> count=<N> credits/unit=<X> total=<Y> percent_of_monthly=<Z>%

Require explicit yes from the user for any single generation over 40 credits or any batch over 100 credits total. Smaller jobs proceed without asking.

Phase 5: Generation

Call the Higgsfield MCP tool. Image jobs return a URL synchronously. Video jobs return a job handle; poll get_generation_status every 8 seconds. Cap polling at 5 minutes. On timeout, surface the job handle and stop polling.

Phase 6: Download and organize

Download every URL to a structured output tree:

output/
  YYYY-MM-DD/
    PROJECT-SLUG/
      images/
        001_nano-banana-pro_4k_2c.png
      videos/
        001_kling-3-0_5s_6c.mp4
      manifest.json

Filename pattern: <seq>_<model-slug>_<format-hint>_<credits>c.<ext>. Write manifest.json incrementally after every generation so a crash mid-batch leaves a readable record. Schema in [references/manifest-schema.md] if you split it out, otherwise inline in this section.

Manifest fields per generation: seq, type, model, prompt, params, credits, url, local_path, duration_seconds, status.

Top-level fields: project_slug, brief, started_at, balance_before, balance_after, generations.

Append a row to output/credit-ledger.csv for every generation: timestamp, project, model, credits, balance_after.

Phase 7: Handoff

If the brief calls for video assembly, write video-config.yaml referencing the downloaded clips and pass control to remotion-video. See references/remotion-handoff.md.

If the brief calls for a document or pitch deck, hand off to docx or pptx with the image paths.

Decision matrix preview

Full matrix in references/model-selection.md. Quick reference:

Brief looks likeModelWhy
Hero image with text on packagingNano Banana ProBest 4K text rendering
Editorial portrait, fashion, Sri Lankan e-commerceSoul V2Free pool, editorial quality
Photorealism with a person holding a productGPT Image 2Unlimited on Plus
Blog hero, illustration, AEO insight coverFlux 2 ProUnlimited on Plus
Concept diagram or abstract ideaSeedream 5.0 LiteVisual reasoning, unlimited
Architecture diagram backdropSeedream 4.5High resolution, unlimited
5-second product motion clipSeedance 2.0Audio-video sync, ~9 credits
Polished 4K social cutKling 3.0Camera language, ~6 credits
8-second narrative beatVeo 3.1Long-form coherence, 40 plus credits
15-second cinematic ad with physicsSora 2Object permanence, 40 plus credits
Variant batch for prompt testingWan 2.6 or Kling 2.5 TurboBudget tier
UGC talking headSeedance 2.0 with lip-syncSingle pass
Consistent character across multiple shotsSoul Character then any modelCharacter ID persists

Credit cost summary

Approximate, verify current numbers in references/credit-costs.md.

TierModelsCost
Unlimited on PlusFlux 2 Pro, Seedream 4.5, Seedream 5.0 Lite, GPT Image 2, Kling O1 Image, Nano Banana 2 (2K)0 credits
Free pool (5,000 monthly)Soul V2, Cinema Studio, Soul Cinema0 credits until pool exhausted
Light paidNano Banana Pro~2 per image
Mid paid videoKling 3.0, Wan 2.6, Hailuo 025 to 6 per clip
Heavy paid videoSeedance 2.0~9 per clip
Premium paid videoVeo 3.1, Sora 240 to 70 per clip

Output folder structure

Every project gets its own folder under output/YYYY-MM-DD/PROJECT-SLUG/. manifest.json is the source of truth. output/credit-ledger.csv aggregates spend across all projects.

Engineering standards (non-negotiable)

  1. Root-cause fixes only. Read MCP error payloads. No frontend patches when the MCP returns errors.
  2. Smoke tests verify real generation. A 1-credit Flux 2 Pro probe with file download is the smoke test, not a claude mcp list health check.
  3. No silent fallbacks. If Higgsfield errors, surface it. Never substitute another provider without explicit user opt-in.
  4. Verify credit balance before any batch over 50 credits.
  5. Maintain manifest.json per project and credit-ledger.csv across the workspace.
  6. Confirm with the user before any single generation over 40 credits or any batch over 100 credits.

Hard constraints

  • Never queue a job that would push balance below 20 credits without explicit confirmation.
  • Never silently fall back to another provider on Higgsfield error.
  • Never proceed past Phase 4 without printing the cost line.

Composes with

  • Runs alongside mobile-app-scaffold for App Store screenshot generation.
  • Hands off to remotion-video for clip assembly with TTS.
  • Hands off to docx and pptx for asset embedding in deliverables.
  • Hands off to frontend-design for hero image generation in web projects.

References

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.