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Higgsfield

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robonuggets
higgsfield

One MCP, 30+ image and video models. Use this skill when the user wants to generate images or videos via Higgsfield (Seedance 2.0, Sora 2, Veo, Kling, Nano Banana Pro, GPT Image 2, Flux, Hailuo, Soul, Cinema Studio, etc.) without juggling per-provider API keys. Triggers on "higgsfield", "higgsfield mcp", "use higgsfield", or any image/video generation request when the user already has a Higgsfield subscription.

Overview

Publisherrobonuggets
Repositoryhiggsfield-skill
Skill namehiggsfield
Stars
71
Forks
15
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by robonuggets on GitHub. Read the source before you install it.

Installation

Install the Higgsfield AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/robonuggets/higgsfield-skill/tree/main/.claude/skills/higgsfield
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/robonuggets/higgsfield-skill.git /tmp/higgsfield-skill
mkdir -p .claude/skills
cp -r /tmp/higgsfield-skill/.claude/skills/higgsfield .claude/skills/higgsfield
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Higgsfield in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Higgsfield on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Higgsfield is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Higgsfield MCP

One connector, 30+ models. Subscription-billed in credits — no per-provider API keys.

When to use this skill

Only use this skill if the user already pays for a Higgsfield subscription. The whole value is access to 30+ models behind one auth, billed against credits they're already paying for. Don't push a non-subscriber to subscribe for one project.

Three spokes

The skill does three things — keep it scoped to these:

  1. Explore models — what's available, what role each model accepts
  2. Generate image — single or batched
  3. Generate video — including image→video chains

Install

Two ways to connect. Both end at the same place: an authenticated MCP your session can call.

Terminal (Claude Code):

claude mcp add --transport http --scope user higgsfield https://mcp.higgsfield.ai/mcp

Then run /mcp in your session and complete OAuth with the Higgsfield account that owns the subscription.

Claude Desktop app:

Settings → Connectors → Add custom connector → paste https://mcp.higgsfield.ai/mcp → sign in.

After auth — mandatory step:

select_workspace

Generation calls fail silently until a workspace is selected. Always run this once at the start of a session.

Heads-up: MCP tools may not appear in the running session after a fresh install — restart Claude Code / Desktop if /mcp shows higgsfield connected but no tools are visible.

No API keys to manage. No .env. The MCP handles auth.

ALWAYS quote credit cost before generating

Non-negotiable. Before any generate_image or generate_video call, quote:

  • Model + settings
  • Estimated credit cost (use the table below)
  • Current balance
  • Balance after the call

Wait for explicit "go" before firing. Credits ≠ free, and silent burn is the #1 way to ruin trust. Auto mode does not override this.

Cost table (measured, not from docs)

models_explore does NOT return credit costs — they're not in the API. Use this baked table:

ModelSettingsCredits
gpt_image_22K medium~3
nano_banana_22K~11
seedance_1_5480p, 4s~2.4
seedance_1_5480p, 12s~7.2
Video at higher tiers—TBD (measure first run)

Numbers will drift. Verify in the Higgsfield dashboard if a run feels off. Update this table when you measure new ones.

Plan-tier silently gates models

Higher-end models (e.g. seedance_2_0) are blocked on Starter and return a generic "Something went wrong" — no helpful error. If a model errors mysteriously, suspect plan gating before debugging the prompt. Suggest checking balance to infer the user's tier.

Workflow mechanics

Upload is 3 steps, not one. Wrap as a single helper if calling repeatedly:

  1. media_upload → returns a presigned PUT URL + media_id
  2. curl -X PUT the file bytes to that URL
  3. media_confirm({ media_id }) → marks it ready

Generation is async:

  1. Call generate_image or generate_video → returns job_id
  2. Poll job_status({ job_id, sync: true }) — usually resolves in 1–2 polls (~10–20s for images, longer for video)

Result fields: always pull rawUrl (PNG / source). minUrl is just the webp preview.

One ref, many gens — an uploaded media_id survives the session. Reuse it across calls instead of re-uploading.

Parallel jobs work fine — fire multiple generate_image calls and poll independently.

Reference passing

Schema is medias: [{ value, role }] (not reference_images). value accepts three forms:

  • media_id — from media_upload / media_confirm
  • job_id — output of a prior generation, used as input to the next. Killer feature for image→video chains — generate a still, feed its job_id straight into generate_video without re-uploading.
  • https:// URL — any public image URL

Role taxonomy varies per model

Always run models_explore action=get for a model before crafting the call. Roles are not consistent:

ModelAccepted roles
Seedance 1.5start_image, end_image
Seedance 2.0full set (image, start_image, end_image, video, audio)
Kling 3.0start_image only
Nano Banana Pro / GPT Image 2image

Pass the wrong role and the call rejects.

Seedance 1.5 duration trap

If you omit duration, Seedance 1.5 silently defaults to 12 seconds — 3× the cost of a 4s clip. Always pass duration explicitly.

Pricing footnotes

  • Plus plan: $39/month, 1000 credits — sweet spot for ad workloads
  • Top-up packs ($5 / 100 credits) expire in 90 days — don't stockpile
  • Verify exact per-call credit cost in the Higgsfield dashboard before committing to a workflow swap

Failure rules

  • Don't silently fall back from ref-to-video to text-to-video — losing the visual anchor defeats the workflow. Surface the failure.
  • Don't retry the same input on the same model when a content-policy check trips — propose changing the input or model.
  • If the MCP errors out, check /mcp to confirm the connection is still live. Subscription lapses break auth.

Models exposed

30+ behind one URL. Highlights:

CategoryModels
ImageNano Banana Pro, GPT Image 2, Flux, Seedream
VideoSeedance 2.0, Sora 2, Veo, Kling, Hailuo
Higgsfield exclusivesSoul (character consistency), Cinema Studio

Limits: images up to 4K, video up to 15 sec.

Frequently asked questions

What does the Higgsfield AI skill do?

One MCP, 30+ image and video models. Use this skill when the user wants to generate images or videos via Higgsfield (Seedance 2.0, Sora 2, Veo, Kling, Nano Banana Pro, GPT Image 2, Flux, Hailuo, Soul, Cinema Studio, etc.) without juggling per-provider API keys. Triggers on "higgsfield", "higgsfield mcp", "use higgsfield", or any image/video generation request when the user already has a Higgsfield subscription.

Why use Higgsfield on TypingMind?

Because you install it once and use it with any model. Higgsfield is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Higgsfield in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/robonuggets/higgsfield-skill/tree/main/.claude/skills/higgsfield. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Higgsfield?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Higgsfield?

As many as you like. As long as a model supports skills, you can use Higgsfield with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Higgsfield AI skill free?

It is published on GitHub by robonuggets. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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