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Get Stats

get_stats
Read-onlyIdempotent

Fetch email sending statistics (delivered, opens, clicks, bounces, etc.) for a date range. Example: get_stats({ start_date: "2024-01-01", end_date: "2024-01-31", _apiKey: "SG.xxx" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyYesSendGrid API key (SG.xxx)
end_dateNoOptional end date in YYYY-MM-DD format. Defaults to today.
start_dateYesStart date in YYYY-MM-DD format, e.g. "2024-01-01"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is already covered. The description adds value by enumerating the metrics returned and providing a concrete call example, which helps the agent understand the scope. It doesn't mention rate limits or pagination, but for a read-only stats endpoint with full annotation coverage, this is solidly helpful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: the first states what it does, the second gives an example. Front-loaded and efficient with no filler. The example is somewhat redundant given the schema examples already exist, but it doesn't waste much space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the description needn't explain return values. Annotations cover the safety profile. The parameter documentation is complete in the schema. The only gap is the lack of differentiation from get_bounces, which is a sibling routing concern rather than a fundamental incompleteness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters with formats and defaults. The description's example repeats the format but adds no syntax or constraint information beyond what the schema provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource: 'Fetch email sending statistics'. The parenthetical enumerates the specific metrics returned (delivered, opens, clicks, bounces), which is clearer than a generic 'get stats'. However, it does not differentiate from the sibling get_bounces, which overlaps with one of the enumerated metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives. The sibling get_bounces overlaps directly with one of the listed metrics (bounces), so a routing sentence distinguishing aggregate stats from per-category tools would be valuable. The description simply describes what it does without usage context.

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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