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Brand

brand
Read-only

A company's brand from its domain: logos for light and dark backgrounds, its real colours, name, description and socials. Answers 'what is this company' far better than a raw page dump.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesThe company domain, e.g. stripe.com. A full URL works too.

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare this as read-only, non-destructive, and open-world, so the description only needs to add behavioral detail beyond that. It does so by enumerating the returned brand elements and framing the output as a semantic answer rather than a raw dump. No contradictions with annotations are present.

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 sentences with no filler: the first lists the tool's output scope, and the second provides a concise comparative value statement. The key concept 'brand' appears immediately, making the description easy to parse.

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 one-parameter read-only tool, the description sufficiently conveys what the caller gets and why it is useful, while annotations cover the safety profile. It does not specify output format or failure behavior, but with no output schema these are not critical gaps for this simple tool.

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?

The input schema already documents the only parameter thoroughly, including an example and the note that a full URL works. The description only repeats the notion of 'domain' without adding new semantics, so a baseline score of 3 is appropriate.

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 identifies the resource (a company domain) and the concrete returned attributes (logos, colours, name, description, socials), making the tool's purpose clear. It lacks an explicit verb like 'retrieve' and does not directly distinguish itself from the sibling 'logo' tool, but the 'company's brand' framing is specific enough.

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 phrase 'Answers what is this company far better than a raw page dump' implies using this tool when the goal is brand/company identity rather than raw scraping or screenshots. However, it never explicitly states when to use this tool versus the eight sibling tools or provides any exclusion criteria.

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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TDQS

A3.6/5.0
Disambiguation3/5

Most tools target distinct output types like search results, screenshots, images, or styleguides, but scrape and extract overlap significantly in pulling structured data from URLs. Brand and logo also intentionally overlap, with logo being a cheaper subset, though the descriptions do help clarify when to use each.

Naming Consistency3/5

All tool names are short and lowercase, but they mix imperative verbs like extract, map, scrape, and search with noun-style names like brand, images, logo, and styleguide. There is no consistent verb-noun pattern, though the names remain readable and memorable.

Tool Count4/5

Nine tools is a reasonable size for a web data-fetching server, and each tool covers a plausible retrieval mode. The set is not perfectly lean due to some functional overlap, but nothing feels excessive or redundant enough to hurt usability.

Completeness4/5

The toolset covers discovery via search and map, content extraction via scrape and extract, and visual/asset needs via screenshot, images, brand, logo, and styleguide. Minor gaps like PDF extraction or raw HTML retrieval exist, but agents can usually work around them.

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