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Brand-System

@brandsystem/mcp

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brand_extract_visual

Extract brand colors, fonts, and visual personality from JS-rendered websites by taking a screenshot and analyzing computed styles. Use when standard extraction yields low quality.

Instructions

Screenshot a website and extract brand colors, fonts, and visual personality using headless Chrome. Returns the screenshot as an image for your visual analysis PLUS computed styles from rendered elements. Use when brand_extract_web yields LOW quality (e.g. JS-rendered sites like Basecamp), when you need visual context for brand personality, or when CSS parsing misses colors. Requires Chrome/Chromium installed. NOT for Figma extraction — use brand_extract_figma instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesWebsite URL to visually extract brand identity from (e.g. 'https://basecamp.com')
mergeNoIf true and .brand/ exists, merge visual results into existing core-identity.yaml. If false, return data only without writing.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses the use of headless Chrome, requirement of Chrome/Chromium, and that it returns a screenshot and computed styles. However, it does not mention the behavior of the 'merge' parameter (whether it writes to disk) in the description, though that is in the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with five sentences covering purpose, output, usage guidance, requirement, and exclusion. Front-loaded with the main action, no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers main functionality, output, usage context, and prerequisites. However, it omits the merge parameter's write behavior, which is only in the schema. Given no output schema, the description adequately explains return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already explains both parameters. The description does not add additional meaning beyond what the schema provides for the parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool screenshots a website and extracts brand colors, fonts, and visual personality using headless Chrome. It distinguishes itself from siblings by specifying when to use it (e.g., for JS-rendered sites) and that it is not for Figma extraction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: when brand_extract_web yields low quality, need visual context, or CSS parsing misses colors. Provides an anti-pattern: 'NOT for Figma extraction — use brand_extract_figma instead.' Also notes a prerequisite (Chrome/Chromium installed).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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