higgsfield-real-estate

higgsfield-real-estate is a skill for Claude Code from pixelab-ch/higgsfield-skills. It costs 87 tokens per session (1,581 once invoked), scanned A, original, MIT.

A video-prompting skill for creating property, architecture, and interior-design showcase videos with Higgsfield, an AI video-generation service. It supports text descriptions and optional reference photos.

In plain words
What is it for?
Use it for property tours, real-estate listings, architecture showcases, interior-design presentations, home-staging content, and property marketing videos.
Why use it?
It prepares the video settings and model choice for property-focused footage, including supported aspect ratios and durations. This avoids manually adapting a general video prompt to real-estate work.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it for property tours, real-estate listings, architecture showcases, interior-design presentations, home-staging content, and property marketing videos.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pixelab-ch/higgsfield-skills/15-real-estate
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 pixelab-ch/higgsfield-skills --skill 15-real-estate
Clone the repo
git clone --depth 1 https://github.com/pixelab-ch/higgsfield-skills

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.

agentmods badge for higgsfield-real-estate

README.md
[![agentmods](https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/15-real-estate/github.svg)](https://agentmods.dev/skills/pixelab-ch/higgsfield-skills/15-real-estate)
Your own site
<a href="https://agentmods.dev/skills/pixelab-ch/higgsfield-skills/15-real-estate"><img src="https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/15-real-estate/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.

agentmods 80×15 button for higgsfield-real-estate

Your own site · 80×15
<a href="https://agentmods.dev/skills/pixelab-ch/higgsfield-skills/15-real-estate"><img src="https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/15-real-estate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,581 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00087 $0.01581
Opus 5.5 $0.00035 $0.00632
Sonnet 5.5 $0.00017 $0.00316
Haiku 4.5 $0.00009 $0.00158

Measured 1mo ago against content hash e7b4a1c59303, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

higgsfield-real-estate 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 1mo 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.

skills/15-real-estate/SKILL.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Higgsfield Real Estate Skill

What this skill does

Crafts production-ready real estate and architecture showcase video prompts and routes them to the best Higgsfield model for property-grade cinematic output. On request, it assembles the full parameter set, surfaces the credit cost, and — after explicit user confirmation — generates the asset via the opt-in generation flow. Handles both text-to-video (default) and optional image-to-video for properties with reference photography.


Model routing

Primary and fallback video models

cinematic_studio_3_0 (primary) veo3_1 (fallback)
Rationale Dedicated cinematic pipeline; default for all property showcase video Photorealism + native audio when primary is unavailable or voiced narration is needed
Tunable params None — pass only aspect_ratio and duration quality {basic, high, ultra}; model {veo-3-1-preview, veo-3-1-fast}
Aspect ratios 16:9, 9:16, 1:1 16:9, 9:16 only — no 1:1
Duration 4–15 s (continuous range) 4, 6, 8 s (discrete set only — no other values)
Media roles image, start_image, end_image start_image only (max 1)
Native audio No Yes

Routing rule: Use cinematic_studio_3_0 by default. Only fall back to veo3_1 when (1) the primary model is unavailable, or (2) the user wants native audio narration or explicitly photorealistic output and, after being told what they give up, accepts veo3_1's constraints: no 1:1 aspect ratio, discrete durations only (4/6/8 s instead of the continuous 4–15 s range), and start_image only (no end_image). If the user has not been informed of these trade-offs, stay on cinematic_studio_3_0 and let them decide — never switch silently.

MODEL-06 directive: If a parameter is rejected at generation time, call higgsfield:models_explore with the target model name to re-verify the live schema. The live catalog is the authoritative source — never guess parameter values. Full parameter tables: references/model-specs.md.

Read the full file on GitHub · 123 lines

Files

What ships with it

4 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.

  1. 1mo ago First seen · 123 lines · 87 tokens per session scan A e7b4a1c59303

Subscribe to this mod's changes

higgsfield-real-estate is a skill published in the GitHub repository pixelab-ch/higgsfield-skills (10 stars, last pushed 5mo ago), licensed MIT. It adds 87 tokens to every session and 1,581 once invoked, about $0.0003 per session on Opus 5.5. 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.

Related

Other skills, from other repositories

create-short

Create a short-form vertical video (TikTok, Instagram Reels, YouTube Shorts). Optimized 9:16 pipeline with a live Studio preview, auto-captions, hook-first structure, and background music mood selection; renders to MP4 only when you ask.

DojoCodingLabs/remotion-superpowers · 58 tokens

create-video

Full video production pipeline — from a text prompt to a live Studio preview with voiceover, music, sound effects, stock footage, and motion graphics, rendered to MP4 when you ask. The flagship command of Remotion Superpowers.

DojoCodingLabs/remotion-superpowers · 50 tokens

review-video

Review a Remotion video with AI vision. Starts with a cheap local check of rendered still frames, then has TwelveLabs watch the full render and score it against a JSON rubric (pacing, composition, text legibility, audio sync and more) with timestamped fixes, applies the fixes and re-reviews. The feedback loop that…

DojoCodingLabs/remotion-superpowers · 75 tokens

add-captions

Add TikTok-style, karaoke, YouTube or minimal captions to your Remotion video. Gets word-level captions through the official remotion-captions flow (whisper-webgpu, or ElevenLabs Scribe via @remotion/elevenlabs when there's no GPU), or imports the user's SRT with parseSrt, places one official caption element per clip…

DojoCodingLabs/remotion-superpowers · 89 tokens

analyze-footage

Analyze existing video files with TwelveLabs AI. Get a timestamped scene map of your footage, ask questions about it, find specific moments across a library, and get the best clips with timestamps for Remotion.

DojoCodingLabs/remotion-superpowers · 47 tokens

generate-clip

Generate AI video clips for your Remotion project. Create unique footage from text descriptions or animate still images into video — no stock footage needed.

DojoCodingLabs/remotion-superpowers · 32 tokens