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

With readOnlyHint and idempotentHint annotations already covering safety, the description adds useful behavioral details: omitting metrics returns summary figures, and larger series like daily, tools, clients, follows, and sparklines are only returned when explicitly named. It also communicates the cost-conscious behavior of returning exactly what is requested.

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 compact, front-loads the core purpose, and every sentence earns its place. The first sentence establishes what the tool returns; the second gives actionable usage guidance without redundancy or filler.

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 output schema and full parameter coverage, the description is largely complete for correct invocation: it explains the default return behavior, how to request specific metrics, and what larger series are available. It does not add explicit sibling differentiation or mention edge behavior beyond parameters, but nothing critical is missing for an agent to call it correctly.

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 schema already documents all parameters thoroughly, so the baseline is 3. The description goes beyond the schema by explaining the selective-return behavior, giving a concrete example (metrics: ["calls"]), and warning against pulling the full overview unnecessarily. This adds meaningful guidance for using the metrics parameter correctly.

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 identifies the tool as returning headline metrics for one MCP over a date range and enumerates the specific metrics included. It does not explicitly name or compare against sibling tools like get_usage or get_insights, so it misses the strongest form of differentiation, but the scope and metric list make the purpose unambiguous.

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 implies when to use it (when you need headline metrics for a single MCP over a date range) and provides concrete guidance on requesting only needed metrics. However, it does not explicitly explain when to choose this tool over its get_* siblings or state any exclusions, leaving some selection guidance to inference.

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