mk_brandsRetrieve MasterKala brand slugs for catalog browsing and filters. Filter by name to find the exact slug needed for product search.
List the brands MasterKala sells with their slugs (about 135).
Use to get the brand slug for mk_browse / mk_filters ('anker-fa', 'mcdodo').
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Optional filter on the brand name, English only, e.g. 'xiaomi' or 'anker'. |
Changes observed during successful MCP inspections.
v0.3.0Input schema / properties / query / titleRemoved value: -"Query"Input schema / titleRemoved value: -"mk_brandsArguments"Output schema / (root)Previous value: -{
- "additionalProperties": true,
- "title": "mk_brandsDictOutput",
- "type": "object"
-}New value: +nullv0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already covers the safety profile, so the description only needs to add context. It adds the result size (~135) and the value format (slugs), but says nothing about pagination, ordering, or what non-matching queries return.
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?
Two short sentences, zero filler, with the core purpose front-loaded and the consumption guidance second. Nothing could be removed without losing signal.
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 simple read-only listing with no output schema, the description supplies enough: what it returns, roughly how many, and the identifier format that downstream tools need. Return shape and pagination are left implicit, which is a minor gap given the tool's simplicity.
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 single 'query' parameter already has a full schema description (100% coverage) covering its optionality, min length and English-only constraint. The description adds no further parameter detail, so the baseline 3 applies.
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?
Specific verb+resource: 'List the brands MasterKala sells with their slugs', and it quantifies scope ('about 135') and gives concrete slug examples ('anker-fa', 'mcdodo'). This clearly separates it from siblings like mk_categories or mk_filters.
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?
Explicitly states a use case and names the downstream siblings that consume its output ('Use to get the brand slug for mk_browse / mk_filters'). It does not state when not to use it or compare against other discovery tools, so it stops short of the top score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.