What is higgsfield-generate?

A workflow for generating images, videos, 3D assets, and audio through Higgsfield AI, including branded advertising materials.

It is for creating visual and audio assets, branded ads, avatars, product media, hooks, and video score summaries.

It handles model selection and job execution for different media types, while also supporting video virality scoring.

higgsfield-generate — Skill for Claude Code by S3YED

Install

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.

Any agent

npx skills add S3YED/appie-kit --skill higgsfield-generate

Clone the repo

git clone --depth 1 https://github.com/S3YED/appie-kit

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/s3yed/appie-kit/higgsfield-generate/github.svg)](https://agentmods.dev/skills/s3yed/appie-kit/higgsfield-generate)

Your own site

<a href="https://agentmods.dev/skills/s3yed/appie-kit/higgsfield-generate"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/higgsfield-generate/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/s3yed/appie-kit/higgsfield-generate"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/higgsfield-generate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 334 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 5,737 The whole file, excluding the scripts and references it only reads on demand.

Security scan C 2 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 92% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.00334	$0.05737
Opus 5	$0.00167	$0.02868
Sonnet 5	$0.00067	$0.01147
Haiku 4.5	$0.00033	$0.00574

Measured 9d ago against content hash 4891082cc041, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade C, and why

higgsfield-generate scanned grade C with 2 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 9d 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.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh

Origin

This is a copy

92% identical to higgsfield-generate — 85 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/content/higgsfield-generate/SKILL.md · 319 lines

How it starts

The opening of the file, as written. The whole thing — 319 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Higgsfield Generate

Submit jobs to any Higgsfield model. Wraps the higgsfield CLI. Covers generic image/video/3D/audio generation, Marketing Studio (branded ads, avatars, products, hooks, settings), and, secondarily, Virality Predictor video scoring.

Step 0 — Bootstrap

Before any other command:

If higgsfield is not on $PATH, install it:

curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh

If higgsfield account status fails with Session expired / Not authenticated, ask the user to run higgsfield auth login (interactive) and wait for confirmation.

UX Rules

Be concise. No raw IDs, no JSON dumps in chat. Print the media URL for generated assets, or the text summary for Virality Predictor.
No internal jargon. Don't narrate "calling higgsfield cost", "polling job".
Detect the user's language from the first message and reply in it. Technical args (--aspect_ratio 16:9) stay English.
Don't batch-ask. Pick a sane default model and ask one thing at a time only if genuinely missing.
Don't pre-estimate cost or optimize for cheaper models unless the user asks. Prefer the quality default first.
Pass --wait to generate create so the command blocks until done and prints the result URL itself. Avoid the two-step create → wait pattern.

Discovery guardrail

When looking for a Higgsfield feature/model, do not rely only on semantic search or CLI --help. First run an unfiltered model list, then inspect likely job_set_type names. If the user says a model exists but search returns no results, trust that signal and verify with the full model list before answering.

Workflows are separate from models. Discover them with higgsfield workflow list and inspect params with higgsfield workflow get <workflow_name>.

Virality Predictor is exposed as:

Customer-facing name: Virality Predictor
Technical job_set_type: brain_activity
Category/output: text report. This is video-in/text-out analysis, not a text/chat generation model.
Input: uploaded video
Purpose: finished-video hook, attention, retention, and virality analysis

Read the full file on GitHub · 319 lines

Files

What ships with it

12 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.

Changes

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.

9d ago First seen · 319 lines · 334 tokens per session scan C 4891082cc041

Subscribe to this mod's changes

higgsfield-generate is a skill published in the GitHub repository S3YED/appie-kit (9 stars, last pushed 17d ago), licensed MIT. It adds 334 tokens to every session and 5,737 once invoked, about $0.0017 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). It is 92% identical to higgsfield-generate, differing in 85 lines, and is treated as a copy.

Creative and media Marketing and SEO agent-skills ai-agent ai-employee ai-employee-kit anthropic automation

browser-edge-cases

SOP for debugging browser automation failures on complex websites. Use when browser tools fail on specific sites like LinkedIn, Twitter/X, SPAs, or sites with Shadow DOM.

aden-hive/hive · 40 tokens

aws-patterns

Lambda best practices, S3 event patterns, SQS/SNS fanout, and DynamoDB access patterns for serverless AWS architectures.

vibeeval/vibecosystem · 31 tokens

review

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use…

stevesolun/ctx · 95 tokens

agents-md-protocol

Create or review an AGENTS.md file so coding agents get stable repo-local instructions: environment setup, testing, style, security boundaries, PR policy, and handoff rules. Use when a repo lacks durable agent guidance or when a custom harness needs a predictable context file.

stevesolun/ctx · 59 tokens

investment-memo-generator

Investment memo creation combining financial analysis, document generation, and structured templates. Use when creating investment memos, pitch decks, deal summaries, or investment committee materials.

travisjneuman/.claude · 37 tokens

python-memory-safe-scripts

Memory-safe Python script patterns for long-running processes under systemd MemoryMax constraints. Covers allocator purge (mimalloc/glibc malloctrim), HTTP response lifecycle, DataFrame cleanup, thread-local connection reuse, and periodic GC cadence. Battle-tested through 5 OOM optimization cycles on production GPU…

terrylica/cc-skills · 197 tokens

higgsfield-generate