get_statsRetrieve monthly workspace event statistics: accepted, deduplicated, and failed events, plan and free-allowance usage, plus the traffic split between human/app and agent/bot sources.
This month's accepted, deduplicated and failed events for the workspace, plan and free allowance, and the usage split between human/app and agent/bot traffic (both billed the same).
| 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?
With no annotations, the description carries the burden and does add useful context: the data is scoped to this month, failed events are counted, deduplication is applied, and bot traffic is billed the same as human traffic. It does not discuss permissions, freshness, or return format, but for a read-only stats tool the disclosed behavioral nuances are substantial.
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?
The definition is a single dense sentence that front-loads the time scope and then enumerates the metrics. It is efficient though somewhat packed; every clause adds relevant content.
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 and no annotations, so the description must convey what the tool returns. It names the key metrics and billing split, which is enough for an agent to understand the response's substance, though it does not describe response structure or units.
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 has zero parameters, so there are no parameter semantics to explain; the baseline for 0 params is 4. The description does not need to compensate for any schema gaps.
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 specifies the resource clearly: this month's accepted, deduplicated, and failed events, plan/free allowance, and human/app vs agent/bot usage split. It is specific enough to distinguish from track_event (which records events) and test_meta_connection, though it uses a noun phrase rather than an explicit verb.
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 implied: this is the tool for checking current-month usage stats. There is no explicit when-to-use guidance, no exclusions, and no direct mention of when to choose it over the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.