Given an Avahit product id, return what Avahit itself observed about its price: current price and when it was last verified against the store, the lowest and highest price seen with dates, the average, how many checks and since when. Amazon products have no history — Amazon's licence forbids keeping their prices longer than 24 hours.
| Name | Required | Description | Default |
|---|---|---|---|
| productId | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does meaningfully more than restate the name: it discloses the exact data returned and a real data-governance constraint (Amazon prices are not retained beyond 24 hours due to licensing, so Amazon products return no history). It does not cover auth requirements, rate limits, or behavior on an unknown/invalid product id.
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?
One dense, front-loaded sentence that opens with the precondition and payload, then appends the Amazon limitation where it belongs. Every clause carries information, though the long comma-separated enumeration of return fields makes it heavier than it needs to be.
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?
There is no output schema, so the description must describe return values, and it does so thoroughly, including dates, average and check counts. The main remaining gap is error/edge behavior for an unknown product id, but for a single-parameter read tool this is close to complete.
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 0%, so the description must compensate for the single undocumented parameter. It does: 'productId' is defined as an Avahit product id, which is more specific than the bare 'string' type in the schema, and the Amazon note clarifies that non-Avahit ids will not produce history. Format/validation details are still absent.
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?
States a specific verb (return/give) and resource (price history for an Avahit product id) and enumerates exactly what comes back: current price, last-verified date, low/high with dates, average, check count and start date. The scope qualifier 'what Avahit itself observed about its price' implicitly separates it from search_products and compare_alternatives, so an agent can tell what kind of tool this is without opening the schema.
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 by the required input ('Given an Avahit product id'), and the Amazon caveat signals one case where the tool yields no history. There is no explicit statement of when to call this versus compare_alternatives or search_products, and no prerequisites are spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.