Retrieve Unibox counts by label, mailbox, and campaign to measure reply volume and prioritize follow-ups.
Unibox counts by label, mailbox and campaign
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": "get_unibox_filters"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden and mostly fails it: it does not say the operation is read-only, what permissions are needed, whether results are scoped to a time range, or anything about the response shape. It only hints at the grouping dimensions of the returned data.
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?
It is a single short fragment with no filler, so it is not verbose. However, given the complete absence of annotations and output schema, this level of terseness is more under-specification than disciplined conciseness.
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 zero-parameter read tool with no output schema, the description's mention of counts grouped by label, mailbox and campaign serves as the only return-value signal, which is useful. Still, it omits when to use it and any behavioral context, so it is only minimally 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?
The tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description introduces no parameter-related confusion.
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 phrase names a resource and the grouping dimensions ('Unibox counts by label, mailbox and campaign'), which tells an agent roughly what data comes back. But there is no verb, and the name says 'filters' while the description says 'counts', so it is unclear whether it returns filter options or aggregated counts. That ambiguity leaves the purpose only vaguely pinned down.
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?
Nothing states when to call this versus siblings like get_overview, get_campaign_stats, or list_mailboxes, nor are any prerequisites or exclusions mentioned. The agent must infer usage entirely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.