Generate a recommendation set for a tenant based on a natural-language query.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural-language recommendation request | |
| tenant | Yes | Merchant domain, e.g. demo.suggestapi.com |
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?
With no annotations, the description carries the full burden but only states that it generates a recommendation set. It does not disclose whether the operation is read-only, whether it has side effects, any authentication requirements, or what the output structure looks like.
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 clear, front-loaded sentence that states the action and scope with no unnecessary detail. Every word earns its place.
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 two-parameter tool with full schema coverage, the description is minimally viable. However, it omits usage context and behavioral details such as the expected output shape or when to prefer a sibling tool, leaving the agent to infer some necessary context.
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% and both parameters already have meaningful descriptions. The tool text adds minimal extra meaning beyond framing query as a natural-language request and tenant as the scoping domain.
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 identifies the tool's function: generating a recommendation set from a natural-language query for a tenant. It is distinct in resource and intent from sibling tools like search and compare, though it does not explicitly name them.
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?
No guidance is provided on when to use this tool versus sibling tools such as search, compare, or product_lookup. There are no conditions, exclusions, or alternative references in the description.
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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Each tool has a distinct role: search is broad discovery, recommend generates recommendations, product_lookup retrieves a single record, and compare evaluates multiple objects. The only meaningful overlap is between search and recommend, but their descriptions make the different return purposes clear.
Three tools use clear single-word verb names (compare, recommend, search), while product_lookup combines a noun and verb. This is a minor structural inconsistency rather than a chaotic mix, and all names are instantly understandable.
Four tools form a compact, well-scoped set for a suggestion and discovery API. Each tool covers a distinct user intent without redundancy or unnecessary surface area.
The tool set covers the core query workflows for the domain: locate items, retrieve a canonical record, get recommendations, and compare options. Management features are absent but appear outside the read-only SuggestAPI scope, so there are no meaningful gaps for an agent.