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brand

Extract brand identity elements like colors, fonts, logos, and favicons from any website's HTML and CSS for analysis or implementation.

Instructions

Extract brand identity (colors, fonts, logo, favicon) from a website's HTML and CSS. Automatically falls back to the webclaw cloud API when bot protection is detected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to extract brand identity from
Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. It adds valuable behavioral context about the automatic fallback to webclaw cloud API when bot protection is detected, which is critical for dependency understanding. However, it omits other important behavioral details like rate limits, authentication requirements, or what happens when extraction partially fails.

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?

Two efficiently structured sentences with zero waste. The first front-loads the core purpose with specific deliverables, while the second adds critical operational context (fallback behavior). Every word earns its place.

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?

For a single-parameter tool with full schema coverage and no output schema, the description adequately covers the primary unusual behavior (external API fallback). It could be improved by briefly mentioning the expected return structure or noting that this is a read-only operation, but the essential functional and behavioral context is present.

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

Parameters4/5

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

Despite 100% schema coverage (baseline 3), the description adds meaningful semantic context by specifying extraction occurs from 'HTML and CSS', implying the URL should point to a styled webpage rather than arbitrary resources. This adds clarity beyond the schema's basic 'URL to extract brand identity from'.

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

Purpose4/5

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

The description clearly states the specific extraction target (colors, fonts, logo, favicon) using the verb 'Extract', making the scope well-defined. However, it lacks explicit differentiation from the sibling 'extract' tool, which could cause confusion about when to choose 'brand' over general extraction.

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

Usage Guidelines3/5

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

The description provides implicit guidance by specifying the domain (brand identity extraction) and mentions automatic fallback behavior when bot protection is detected. However, it lacks explicit 'when to use' guidance contrasting with siblings like 'extract', 'scrape', or 'crawl'.

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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