brandsystem-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it performs a screenshot operation, extracts visual brand elements, returns both an image and computed styles, and has specific use cases and exclusions. It doesn't mention error handling, performance characteristics, or authentication needs, but covers the core operational behavior well.

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

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

The description is efficiently structured with three sentences that each serve distinct purposes: stating the core functionality, specifying use cases, and providing exclusions/prerequisites. There's no wasted text, and the most critical information (what it does and when to use it) is front-loaded.

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

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

For a tool with no annotations and no output schema, the description provides good contextual completeness. It explains what the tool does, when to use it, what it returns, and important constraints. It could be more complete by describing the output format in more detail (e.g., structure of 'computed styles'), but given the complexity and lack of structured output documentation, it covers the essentials well.

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

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

Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema descriptions. The baseline score of 3 is appropriate when the schema does the heavy lifting for parameter documentation.

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

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

The description clearly states the tool's purpose with specific verbs ('Screenshot a website and extract brand colors, fonts, and visual personality') and distinguishes it from siblings by contrasting with 'brand_extract_web' and 'brand_extract_figma'. It explicitly mentions the resource ('website') and method ('using headless Chrome').

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

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

The description provides explicit guidance on when to use this tool ('when brand_extract_web yields LOW quality', 'when you need visual context for brand personality', 'when CSS parsing misses colors') and when not to use it ('NOT for Figma extraction — use brand_extract_figma instead'). It also mentions prerequisites ('Requires Chrome/Chromium installed').

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