Borrowing it
Nothing to install: this file belongs to pixelab-ch/higgsfield-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/pixelab-ch/higgsfield-skills/main/CLAUDE.mdgit clone --depth 1 https://github.com/pixelab-ch/higgsfield-skillsWrote 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.
[](https://agentmods.dev/instructions/pixelab-ch/higgsfield-skills/claude-md)<a href="https://agentmods.dev/instructions/pixelab-ch/higgsfield-skills/claude-md"><img src="https://agentmods.dev/badge/instructions/pixelab-ch/higgsfield-skills/claude-md/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.
<a href="https://agentmods.dev/instructions/pixelab-ch/higgsfield-skills/claude-md"><img src="https://agentmods.dev/badge/instructions/pixelab-ch/higgsfield-skills/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.03994 | $0.03994 |
| Opus 5 | $0.01997 | $0.01997 |
| Sonnet 5 | $0.00799 | $0.00799 |
| Haiku 4.5 | $0.00399 | $0.00399 |
Grade A, and why
higgsfield-skills CLAUDE.md scanned grade A with 0 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 10d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project
Higgsfield Skills — Multi-Model Prompt & Generation Toolkit
A collection of Claude Agent Skills that turn Claude into an expert prompt engineer for AI image and video generation on the Higgsfield platform. Each skill covers a creative style or use case (cinematic, anime, fight scenes, e-commerce ads, product 360°, real estate, etc.), produces a production-ready prompt, maps it to the most appropriate Higgsfield model, and can optionally submit the generation directly through the Higgsfield MCP server. It is the rearchitecture of the existing higgsfield-seedance2-jineng repo, which today only targets a single model (Seedance 2.0) and only outputs static prompt text.
Core Value: Given a creative request, Claude produces a model-correct, spec-accurate prompt and (on explicit confirmation) generates the asset on Higgsfield — without the user needing to know which of the ~38 Higgsfield models to pick or what parameters each accepts.
Constraints
- Platform: Higgsfield only — all generation goes through the Higgsfield MCP server already present in the environment
- Compatibility: Must follow the Claude Agent Skills format (YAML frontmatter
name+description;SKILL.md+ optionalreferences/) so skills load in both Claude Code and Desktop - Cost: Generation consumes Higgsfield credits → never generate without explicit user confirmation
- Accuracy: Per-model specs must match what
models_explorereports, not invented numbers - Languages: English + French only
- Source of truth for model constraints: the live
models_explorecatalogue, not hardcoded assumptions that can drift
Technology Stack
1. SKILL.md Frontmatter Specification
Required fields
| Field | Required | Limit | Rules |
|---|---|---|---|
name |
Recommended (not strictly required — defaults to directory name) | 64 chars | Lowercase letters, numbers, hyphens only. No XML tags. Reserved words "anthropic" and "claude" forbidden. Must match the directory name when set. |
description |
Recommended | 1024 chars | Non-empty. No XML tags. Write in third person. Include what it does AND when to use it. Put key use case first — combined description + when_to_use is truncated to 1,536 chars in the skill listing. |
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.
- 10d ago First seen · 267 lines · 3,994 tokens per session scan A d0393a2aa978
higgsfield-skills CLAUDE.md is an instructions file published in the GitHub repository pixelab-ch/higgsfield-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 3,994 tokens to every session, about $0.0200 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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