explain

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

Annotations provide readOnlyHint=true, confirming the tool is read-only. The description adds that it returns statistics about execution, which is beneficial for understanding its output. No contradictions; it complements annotations well.

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 a single, front-loaded sentence (21 words) that directly states the tool's purpose. Every word earns its place, with no redundancy or 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 complexity of the input schema (nested method parameter with many options) and the presence of an output schema, the description is adequate but minimal. It could mention that the method accepts find, aggregate, or count commands, but the schema already conveys this.

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?

Schema coverage is 100%, with detailed descriptions for all parameters (database, collection, method, verbosity). The tool description does not add meaning beyond what the schema already provides, meeting the baseline for high coverage.

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 it returns statistics about the query optimizer's winning plan execution for a given method. It uses specific verb 'returns statistics' and resource 'execution of the winning plan', distinguishing it from sibling tools that execute queries (find, aggregate, count) rather than explain them.

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 does not explicitly state when to use this tool versus alternatives like find, aggregate, or count. It implies it's for explaining a query, but lacks guidance on prerequisites or exclusions (e.g., when to use executionStats verbosity).

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