pmg_statistics_mailcount

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It states the tool is a read operation and gives parameter constraints, but does not discuss rate limits, error handling, or authentication beyond the config note.

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 description is concise, with each sentence providing useful information. It could be better structured (e.g., bullet points), but there is no wasted text.

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?

Given the existence of an output schema (not shown), the description does not need to detail return values. It covers purpose, key parameters, and config, but lacks typical usage context or examples. It is adequate but not fully comprehensive.

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?

With only 25% schema description coverage, the description adds significant meaning: it explains that timespan is in seconds with a range and default, and that start/end are Unix epoch timestamps mapped to query parameters. This goes beyond the bare schema.

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 clearly states the tool retrieves per-bucket mail count statistics and is a read operation. The name is specific enough to hint at its function, but it does not explicitly distinguish among sibling statistics tools like pmg_statistics_domains or pmg_statistics_mail.

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?

The description mentions the requirement for PROXIMO_PMG_* config and provides parameter details (timespan range, start/end mapping). However, it does not explain when to use this tool over other statistics tools or give any exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.