get_metrics

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

No annotations are provided, so the description carries the burden. It discloses one behavioral trait—previous-period comparison when a date range is set—and lists the core metrics returned. However, it does not mention read-only behavior, return structure, or what happens when neither period nor dates are set, leaving gaps.

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 two short sentences, direct and front-loaded with the metric list. Every word earns its place with no fluff or redundancy.

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?

With 11 parameters, no output schema, no annotations, and 16 sibling tools, the description is too sparse. It lists metrics but does not explain output format, how filters interact, or when to prefer this over siblings, making it incomplete for a tool of this complexity.

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 input schema fully documents all 11 parameters with descriptions, achieving 100% coverage. The description adds no parameter-specific meaning beyond the date-range comparison, so the baseline of 3 applies.

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 returns key metrics (daily users, sessions, events, avg duration) for an app over a period, using a specific verb and resource. However, it does not explicitly distinguish itself from sibling tools like get_periodic_stats or get_top_events beyond the generic 'key metrics' phrasing.

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?

There is no guidance on when to use this tool versus alternatives. The sibling tool names suggest distinctions, but the description neither mentions them nor provides any use-case context or exclusions.

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