Search Avahit's catalog of direct-to-consumer brand products whose prices Avahit re-checks at the store every day. Returns title, current price with the date of the last check, store domain, store rating and a link to the product page on Avahit.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results, 1-20 (default 8) | |
| query | Yes | What the shopper is looking for, e.g. 'white sneakers' |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only declare readOnlyHint and openWorldHint, so the description adds real value beyond them: it discloses data freshness ('re-checks at the store every day') and enumerates the returned fields, including the last-check date. It does not mention rate limits, result ordering, or empty-result behavior, keeping it short of a 5.
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 tight sentences: the first establishes scope and data freshness, the second lists return values. Nothing is repeated from the name or schema, and the most decision-relevant fact (daily price re-checks) is front-loaded.
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 no output schema, the description compensates by listing the returned fields and their meaning (price with last-check date, store domain, rating, product link). Combined with a fully documented input schema and read-only annotations, an agent has what it needs; only result ordering and empty-state behavior are unaddressed.
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%, with both `query` (example provided) and `limit` (range and default) documented in the schema itself. The description adds no syntax, format, or matching-behavior detail for the query parameter, 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?
The description gives a specific verb+resource ('Search Avahit's catalog of direct-to-consumer brand products') and adds a meaningful scope qualifier: prices are re-checked at the store daily. It never names the siblings (compare_alternatives, get_price_history, get_store_sales), so an agent gets a clear purpose but no explicit routing signal.
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?
Usage is only implied – an agent can infer this is the entry point for finding products, but there is no statement of when to use it versus get_price_history or compare_alternatives, nor any prerequisites or exclusions. Minimum-viable guidance rather than explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.