refine-moodboard

Generates single-file HTML moodboards from use-case briefs using LLM-produced design specs.

Updated Feb 16, 2026
One-click install
npx skills add https://github.com/GQAdonis/artifact-refiner-skill --skill refine-moodboard-gqadonis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: refine-moodboard
Source: https://github.com/GQAdonis/artifact-refiner-skill/tree/main/skills/refine-moodboard
Command: npx skills add https://github.com/GQAdonis/artifact-refiner-skill --skill refine-moodboard-gqadonis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Creating a visual moodboard for a new brand or product concept normally requires manual design work; this Skill turns a plain-language brief into a rendered HTML moodboard with palettes, typography, motifs, and tone chips. ## Core Features & Use Cases - LLM-driven spec synthesis: The LLM produces structured JSON containing light and dark palettes, typography, motifs, and tone, validated for hex colors and required fields. - Template rendering: A Minijinja moodboard.html template renders the validated spec into a single self-contained HTML file with inline CSS. - Graceful fallback: When the inference proxy is unreachable or validation fails, it falls back to a placeholder mode using an existing brand's palette or a neutral gray scheme. - Use Case: Given a brief like "fintech dashboard for enterprise CFOs with a minimal, trustworthy aesthetic", generate a moodboard HTML showing color swatches, font specimens, and tone chips to align stakeholders before design work begins. ## Quick Start Ask the assistant to generate a moodboard HTML file for your use case, target audience, and aesthetic keywords, optionally anchored to an existing brand.

Frequently Asked Questions about refine-moodboard

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a moodboard HTML from a text brief?▼

Provide a use case, audience, and comma-separated aesthetic keywords plus an output path. The skill prompts an LLM for a structured JSON spec with palettes and typography, then renders it through a Minijinja template into a single HTML file.

What inputs are required to create a design moodboard?▼

Four arguments are required: --use-case describing the product, --audience describing the target users, --aesthetic with comma-separated keywords, and --output for the HTML path. Optional flags include --brand, --mode, and --palette-mode.

Does moodboard generation work without an LLM endpoint?▼

Yes, it falls back to placeholder mode when the inference proxy is unreachable or validation fails. Placeholder mode uses an existing brand's palette if --brand is supplied, otherwise a neutral gray scheme with system fonts.

How does the skill handle invalid or malicious LLM output?▼

Responses are stripped of markdown fences, rejected if they contain prompt-injection markers like SYSTEM: or IGNORE PREVIOUS, and validated so every palette value is a hex literal and typography includes display, UI, and body entries.

What are the limitations of the generated moodboard?▼

Motif tiles and tone chips contain placeholder text in both modes since visual motif generation is out of scope. Output is limited to a single HTML file with inline CSS containing light and dark palettes.