get_brands
Svi brendovi (Bugaboo, Cybex, Maxi-Cosi, ...) s brojem proizvoda.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| brands | Yes |
Svi brendovi (Bugaboo, Cybex, Maxi-Cosi, ...) s brojem proizvoda.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| brands | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description's only added behavioral content is that each brand is returned with a product count; it says nothing about ordering, completeness, or caching. Against a rich annotation set, that is a modest but real contribution.
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?
A single front-loaded sentence with no filler. The parenthetical examples of brand names are the one embellishment and they earn their place by confirming the expected taxonomy.
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?
With an output schema present, no parameters, and annotations covering the safety profile, the definition is nearly complete for a trivial list endpoint. The remaining shortfall is that it gives no hint about ordering or result volume, and it is written in Croatian while the surrounding tool ecosystem (sibling names) is English.
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 tool takes zero parameters, so the baseline is 4 and there is nothing for the description to compensate for. The schema explicitly sets additionalProperties=false, so no hidden input is expected.
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 states a specific verb+resource: it returns all brands, and it even lists example values (Bugaboo, Cybex, Maxi-Cosi) plus the fact that each entry carries a product count. That is clear enough that an agent knows what comes back, though it never contrasts itself with nearby siblings like get_categories or get_sizes, which also enumerate taxonomy values.
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?
There is no when-to-use or when-not-to-use guidance, and no alternative is named. The agent must infer that this is the lookup for brand identifiers before calling search_products, which is the obvious downstream use but is never stated.
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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