ml_get_item_visitsReturns daily visit counts for a Mercado Livre item over the last N days, up to 150. Use it to track listing traffic trends and identify demand changes over a chosen period.
Read-only. Return daily visit counts for an item over the last N days.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Number of days to look back. | |
| item_id | Yes | Item id, for example MLB000000001. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the leading 'Read-only' is largely redundant. The description does add one genuinely useful behavioral detail beyond the schema: the result is a *daily* breakdown rather than an aggregate total. It says nothing about rate limits, auth scope, or the window boundary semantics (inclusive/exclusive), so with annotations carrying the safety profile a 3 fits.
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, front-loaded, nothing wasted. The only inefficiency is the 'Read-only' clause duplicating readOnlyHint, which costs a few tokens without adding information.
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 two-parameter read tool with a fully documented schema, complete annotations, and no output schema, the description conveys the essential shape of the response (daily counts in a window). It is nearly complete; only the absence of any usage routing among nine siblings leaves a small gap.
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%, so both parameters (item_id with an example, days with default/min/max) are already fully documented in the schema. The description's 'over the last N days' only restates the days parameter and adds no format or semantics beyond it; 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 and resource ('Return daily visit counts for an item') plus the time scope, so an agent can distinguish it from a generic item fetch like ml_get_item. It stops short of naming any sibling for contrast, but the purpose itself is unambiguous.
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?
There is no statement of when to use this tool versus the many siblings (ml_get_item, ml_list_items, ml_get_account). The 'last N days' phrasing implies a time-series analytics use case, but the agent must infer that itself; no exclusions or prerequisites are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.