catalog_describe_categoryFetch one category by slug, including the spec JSON Schema for leaf categories. Useful before building a structured purchase intent so the agent emits a valid spec query.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Slug of the category to describe, e.g. "electronics/phones/smartphones". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions that the tool returns the spec JSON Schema, which is a key behavioral detail beyond the readOnlyHint annotations. It does not contradict the annotations and gives enough information about the expected output to avoid surprises.
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 concise, using two sentences to convey purpose, output, and usage context. There is no unnecessary verbosity, and all information is relevant to the agent's decision-making.
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?
The description provides enough context for an agent to understand not only what the tool does but also why and when to use it. It covers the purpose, output, and a concrete use case, making it self-contained and actionable.
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 only parameter 'slug' is fully described with an example value ('electronics/phones/smartphones') and its purpose is clear from the description. The schema already includes minLength and required, and the description enriches this by showing a realistic usage.
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 verb 'Fetch' and the resource 'one category by slug', specifying that it returns the spec JSON Schema for leaf categories. It distinguishes itself from sibling tools like catalog_list_categories and catalog_get_product by focusing on a single category lookup with schema details.
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 explicitly says 'Useful before building a structured purchase intent so the agent emits a valid spec query', which tells the agent exactly when to use this tool. This provides clear usage guidance without needing to infer from sibling tool names or schemas.
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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