prompt-to-asset: Skill for Claude Code

.claude/skills/brand-consistency/SKILL.md

brand-consistency is a skill for Claude Code from MohamedAbdallah-14/prompt-to-asset. It costs 96 tokens per session (2,033 once invoked), scanned A, original, MIT.

A brand-asset consistency workflow for keeping a logo, app icon, favicon, and illustrations visually related. It uses shared colors, typography, style references, and optional model-specific controls.

In plain words
What is it for?
Use it to build a brand bundle, apply its palette and references during asset generation, and validate whether new assets match the established visual style.
Why use it?
It reduces visual drift when several images are generated at different times or with different image models. It can also check style similarity and color differences against the brand definition.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is MohamedAbdallah-14/prompt-to-asset's own configuration. It tells Claude Code how to work on prompt-to-asset itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything prompt-to-asset configures →

Part of the prompt-to-asset plugin — 13 skills, 1 MCP server shipped together

Reuse

Borrowing it

Nothing to install: this file belongs to MohamedAbdallah-14/prompt-to-asset. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/MohamedAbdallah-14/prompt-to-asset/main/.claude/skills/brand-consistency/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/MohamedAbdallah-14/prompt-to-asset

Made for: Claude Code.

Or install prompt-to-asset, the plugin that ships this one along with the rest of its 13 skills, 1 MCP server.

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 brand-consistency

README.md
[![agentmods](https://agentmods.dev/badge/skills/mohamedabdallah-14/prompt-to-asset/brand-consistency/github.svg)](https://agentmods.dev/skills/mohamedabdallah-14/prompt-to-asset/brand-consistency)
Your own site
<a href="https://agentmods.dev/skills/mohamedabdallah-14/prompt-to-asset/brand-consistency"><img src="https://agentmods.dev/badge/skills/mohamedabdallah-14/prompt-to-asset/brand-consistency/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 brand-consistency

Your own site · 80×15
<a href="https://agentmods.dev/skills/mohamedabdallah-14/prompt-to-asset/brand-consistency"><img src="https://agentmods.dev/badge/skills/mohamedabdallah-14/prompt-to-asset/brand-consistency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,033 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium analysis-evasion · line 1
    Suspicious Unicode normalization or mixed-script content
    Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
How audits are shown
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 $0.00096 $0.02033
Opus 5 $0.00048 $0.01017
Sonnet 5 $0.00019 $0.00407
Haiku 4.5 $0.00010 $0.00203

Measured 12d ago against content hash 38170e487307, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

brand-consistency 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 12d 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.

.claude/skills/brand-consistency/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Brand consistency

Engaged when a user is generating more than one asset for the same brand, or when an existing brand.json / brand.md is in play. Wraps asset_brand_bundle_parse, asset_generate_*, and validation.

BrandBundle shape

palette:
  - { name: primary,   hex: "#0A1F44", usage: mark }
  - { name: accent,    hex: "#FF6B6B", usage: highlight }
  - { name: neutral,   hex: "#FAFAFA", usage: background }
typography:
  primary:   { family: "Geist Sans", fallback: "geometric sans-serif, bold" }
  secondary: { family: "Geist Mono", fallback: "monospace" }
style_refs: ["assets/brand/ref-1.png", "assets/brand/ref-2.png"]
lora:       "assets/brand/brand.safetensors"       # optional Flux/SDXL
sref_code:  "--sref 1234567890"                    # optional Midjourney
style_id:   "uuid-of-recraft-style"                # optional Recraft
do_not:     ["drop shadows", "gradients", "photorealism"]
logo_mark:  "assets/brand/mark.svg"                # canonical mark for composition

Call asset_brand_bundle_parse({ source }) to build this from a brand.md, brand.json, DTCG tokens.json, or AdCP spec.

Palette enforcement per model (strongest → weakest)

Provider Mechanism ΔE2000 typical
Recraft V3/V4 controls.colors: ["#hex", …] (hard enforcement) 1–5
Flux.2 JSON color_palette: ["#hex", …] 3–7
Ideogram 3 style_reference_images (palette swatch PNG) or style_codes 5–10
Midjourney prose color words + --sref <id> --sw 250–400 5–12
gpt-image-1 hex codes in prose, reinforced 2–3× 5–15
SDXL / Flux.1 hex in prose + IP-Adapter palette swatch 5–15
Imagen / Gemini prose + post-process recolor 10–20 (post-fix required)

Fallback that always works: K-means remap in LAB space + ΔE2000 validation. asset_validate flags drift; post-process recolors nearest palette entries.

Style reference management

  • Canonical anchor — one .png or .svg that defines the brand look. Required for consistency across >3 assets.
  • Accepted-asset promotion — after an asset passes validation + user acceptance, add it to style_refs[] so subsequent generations see richer brand context.
  • CSD similarity score — Contrastive Style Descriptor embedding comparison. Threshold: ≥0.72 pass, 0.60–0.72 review, <0.60 fail. Tier-2 validation.
  • Model-specific handles:
    • Midjourney: --sref <image> (loose) vs --cref <image> (character lock) vs --mref <image> (object lock). Use --sw 250 for tight style, --sw 100 for loose brand.
    • Recraft: style_id is a persistent UUID bound to a trained brand style.
    • Flux + IP-Adapter: pass reference image; set ip_adapter_weight: 0.7–0.9 for style, lower for just color.
    • SDXL + LoRA: trigger word in prompt + lora_scale: 0.7–1.0.

Read the full file on GitHub · 138 lines

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. 12d ago First seen · 138 lines · 96 tokens per session scan A 38170e487307

Subscribe to this mod's changes

brand-consistency is a skill published in the GitHub repository MohamedAbdallah-14/prompt-to-asset (19 stars, last pushed yesterday), licensed MIT. It adds 96 tokens to every session and 2,033 once invoked, about $0.0005 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 2026-08-30.

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