get-brand-components

get-brand-components is a skill for Claude Code from octavehq/lfgtm. It costs 160 tokens per session (13,538 once invoked), scanned C, original, MIT.

A tool that studies a company's website and turns its visual style into a reusable component kit. The kit records colors, fonts, spacing, shapes, shadows, and common interface elements such as buttons and cards.

In plain words
What is it for?
Use it to capture a website's brand, create design tokens and reusable components, and produce a gallery, machine-readable manifest, and written brand specification.
Why use it?
It gives later generated pages a consistent visual connection to the chosen brand instead of requiring the design system to be recreated by hand.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the octave plugin — 29 skills, 7 agents shipped together

Good fit Use it to capture a website's brand, create design tokens and reusable components, and produce a gallery, machine-readable manifest, and written brand specification.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/octavehq/lfgtm/get-brand-components
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 octavehq/lfgtm --skill get-brand-components
Clone the repo
git clone --depth 1 https://github.com/octavehq/lfgtm

Made for: Claude Code.

Or install octave, the plugin that ships this one along with the rest of its 29 skills, 7 agents.

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 get-brand-components

README.md
[![agentmods](https://agentmods.dev/badge/skills/octavehq/lfgtm/get-brand-components/github.svg)](https://agentmods.dev/skills/octavehq/lfgtm/get-brand-components)
Your own site
<a href="https://agentmods.dev/skills/octavehq/lfgtm/get-brand-components"><img src="https://agentmods.dev/badge/skills/octavehq/lfgtm/get-brand-components/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 get-brand-components

Your own site · 80×15
<a href="https://agentmods.dev/skills/octavehq/lfgtm/get-brand-components"><img src="https://agentmods.dev/badge/skills/octavehq/lfgtm/get-brand-components.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 160 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 13,538 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 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 $0.00160 $0.13538
Opus 5 $0.00080 $0.06769
Sonnet 5 $0.00032 $0.02708
Haiku 4.5 $0.00016 $0.01354

Measured 11d ago against content hash c556422d0b64, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade C, and why

get-brand-components 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 11d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/render_kit.py, scripts/render.py, scripts/verify-logos.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

- *Use it*: follow the asset-manager download workflow in [`../asset-manager/SKILL.md`](../asset-manager/SKILL.md) — mint the token, then `download-artifact.sh --uuid <uuid> --out "${TMPDIR:-/tmp}"` (files land in `${TMP

Makes network callslowCapability

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

- The result may include a `screenshotUrl` (a signed URL). When present, persist it to `screenshots/` with `curl` so the kit has reference images.
skills/get-brand-components/SKILL.md · 556 lines

How it starts

The opening of the file, as written. The whole thing — 556 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Get Brand Components — Brand-to-Component-Kit Builder

Walks the key pages of a target website, captures screenshots and HTML, derives the brand's design system (colors, typography, spacing, components), and produces a reusable component kit: design tokens (tokens.css), a self-contained component gallery (components.html), a machine-readable manifest (manifest.json), and a human-readable spec (brand-kit.md). Other skills (one-pagers, microsites, battlecards, decks, two-pagers) load this kit to generate outputs that look and feel like the target brand.

Output principles: the kit's component styles stay faithful to the captured brand, but everything this skill authors itself follows the shared principles — presentation principles for visuals (the gallery page's own layout and labels), editorial rules for text (brand-kit.md, summaries).

When to Use

  • User wants to make generated HTML (one-pagers, microsites, decks, battlecards) look like a specific company's brand
  • User provides a domain and asks to "capture the brand", "get the components", or "build a design kit"
  • User wants a reusable, on-brand component library before producing a batch of branded collateral
  • Another skill needs brand tokens/components for a target company and none are saved yet

Usage

/octave:get-brand-components <domain-or-url>     # Walk the site and build a brand component kit
/octave:get-brand-components <domain> refresh    # Force a fresh re-walk, overwriting the cached kit
/octave:get-brand-components list                # List saved brand kits
/octave:get-brand-components show <slug>         # Display a saved kit (and open the gallery)
/octave:get-brand-components export <slug>       # Zip the cached kit to ~/Desktop/<slug>-brand-kit.zip
/octave:get-brand-components delete <slug>       # Remove a saved kit

<domain-or-url> accepts acme.com, https://www.acme.com, or https://www.acme.com/product (a specific seed URL).

Read the full file on GitHub · 556 lines

Files

What ships with it

5 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. 11d ago First seen · 556 lines · 160 tokens per session scan C c556422d0b64

Subscribe to this mod's changes

get-brand-components is a skill published in the GitHub repository octavehq/lfgtm (11 stars, last pushed 21d ago), licensed MIT. It adds 160 tokens to every session and 13,538 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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