get_analytics_group_metadata

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

Description adds value beyond annotations by noting pagination, the return structure, and that it's enterprise-gated (returns 403 on non-enterprise plans). Annotations already cover readOnly, idempotent, and non-destructive hints, so the description fills in operational behavior.

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, front-loaded with the main purpose and return fields. Includes a usage tip and a critical restriction (enterprise-gated). No fluff; every sentence serves a purpose.

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 large number of parameters (32) and existence of an output schema, the description covers the key aspects: pagination, grouping, required inputs, and enterprise restriction. It could mention that the many filter parameters are for narrowing results, but the schema already handles that.

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%, so the description does not need to elaborate on parameters. It mentions the required metadata_key and time window but adds no new semantic information beyond what the schema provides. Baseline 3 is appropriate.

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 retrieves a paginated metadata breakdown grouped by a required metadata_key, listing specific return fields (total_groups, group_count, metadata_groups). It gives concrete use cases (per-environment, per-feature) and distinguishes from siblings by emphasizing the grouping by metadata_key.

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?

Explicitly says 'Use this for custom breakdowns like per-environment or per-feature analysis' and requires passing metadata_key with the time window. No explicit alternatives or when-not-to-use, but the context is clear enough for an AI agent to decide appropriately.

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