Shop-level totals: views, leads, and listing counts by status.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "analytics_summary"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full behavioral burden; it does disclose the aggregation level and the exact metrics returned, which is meaningful for a read-only analytics tool. However, it never states the time window the totals cover (all-time vs. a default period) or data freshness, which is the single most consequential unknown for a totals endpoint.
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 front-loaded clause that identifies the aggregation level first and the metrics second, with zero filler. For a no-parameter tool, nothing more is needed structurally.
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 and no annotations, the description is the only source of return-value information, and it gives a metric list but not the shape of the response (field names, units, whether counts are broken out per status label) or the period covered. It is adequate to know roughly what comes back but not to consume the result confidently.
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 tool takes zero parameters, so the baseline is 4 and there is nothing in the schema for the description to clarify. The absence of any date or filter parameter is worth noting but does not lower the parameter-semantics score.
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 names a specific resource (shop-level totals) and enumerates the metrics returned: views, leads, and listing counts by status. That is far more informative than a tautology, and 'shop-level' hints at the contrast with the listing-scoped sibling analytics_listings, though it never names that sibling explicitly.
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 when-to-use guidance, no prerequisite, and no mention of the obvious alternative analytics_listings. An agent must infer from the words 'shop-level totals' alone that this is the overview tool rather than the per-listing breakdown.
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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