get_metrics

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

Describes return format [{x, y}] but no side effects, auth needs, or limits. With no annotations, description should disclose more behavioral traits (e.g., what happens with empty results or invalid types).

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?

Two sentences: one for purpose, one for format. No fluff, front-loaded with key action and examples.

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?

Despite 7 parameters (4 required), description omits optional filter behavior, default limit, and edge cases. No output schema or annotations to compensate. Incomplete for autonomous agent reasoning.

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 covers 100% of parameters. Description adds context ('top values over a window') but doesn't elaborate beyond schema (e.g., meaning of limit, optional filters). Baseline 3 for high coverage with marginal added value.

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?

Description clearly states the tool returns top values for one dimension over a window, with examples. It distinguishes from siblings like get_stats (aggregate metrics) and get_pageviews (specific event).

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?

Implicitly suggests use for dimension breakdowns, but no explicit when-to-use vs alternatives (e.g., cohort_report, get_stats) or when-not-to-use.

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