scan_brand

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

With no annotations provided, the description carries the burden of documenting behavior, and it does contribute meaningful return-value context by describing the full scan result and its contents. It does not disclose whether the scan is synchronous, whether it has side effects like cached results, or whether it involves external website fetching, which leaves a moderate transparency gap.

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 a single, front-loaded sentence that states the action immediately, then adds return-value detail and concrete examples. There is no redundant wording or filler, and the dashboard reference earns its place by clarifying the shape of the result.

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 one well-described parameter and no output schema, the description gives enough context: the operation, the target, and the return contents. It stops short of documenting scan lifecycle, freshness, or error behavior, but those are minor gaps for such a simple single-parameter call.

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?

The schema already covers brandId with a clear description ('The brand UUID from list_brands'), so schema description coverage is 100%. The free-text description adds no additional parameter-level detail beyond associating the audit with the brand's website, making the baseline score of 3 appropriate.

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 action ('Run a technical audit') and the target (the brand's website), and it names the output domain with concrete examples (schema markup, sitemap, llms.txt). It also distinguishes this tool from siblings like get_insights by scoping it to the 'technical scan view' rather than general insights.

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 implies when to use the tool — whenever the agent needs a technical scan of a brand's website — and reinforces this by pointing to the dashboard's technical scan view. However, it does not explicitly state when not to use it or name an alternative sibling for adjacent tasks, so the guidance is implied rather than explicit.

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