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

readOnlyHint=true already establishes a safe read, so the description is free to add value elsewhere — and it does, by naming the four metric families returned and the GET /v1/metrics/ endpoint. It stops short of mentioning rate limits, max date spans, or pagination behavior for large series.

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?

A single front-loaded sentence that carries the verb, resource, scoping, bucketing, metric list, and endpoint with no filler. Nothing to trim and nothing buried.

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 no output schema, the description usefully serves as the only statement of what comes back (orders, revenue, MRR, active subscriptions), and it covers the date/interval framing. It is nearly complete for a read-only analytics tool; only edge behavior like span limits or empty-window handling is absent.

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 description coverage is 100%, so start_date, end_date, interval, product_id, customer_id and organization_id are all documented in the schema itself. The description only restates the date-range/bucket concept at a high level, adding no syntax or constraint detail beyond the schema — the baseline 3.

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?

States a specific verb (fetch) and resource (revenue and subscription metrics) and enumerates what the metrics are: orders, revenue, MRR, active subscriptions. That is enough for an agent to know this is the aggregate-analytics tool rather than one of the many polar_list_* siblings, though it never explicitly names or contrasts with 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 date-range and interval-bucketing framing implies the analytics use case, but there is no explicit when-to-use, when-not-to-use, or pointer to alternatives such as polar_get_meter_quantities or the list tools. Usage is inferable but not guided.

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