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

readOnlyHint=true already tells the agent this is a safe read. The description adds real behavioral color per metric (contacts = current totals, inbox_users = assignments/closures/response times), but says nothing about response size, rate limits, or default time ranges.

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?

Front-loaded with the verb and scope, then metric definitions, then group rules. Dense but every clause maps to a specific enum or constraint; the long group list is necessary because the schema punts on it rather than padding.

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 partially compensates by saying what each metric reports, and it documents the per-metric group constraint fully. A 6-parameter analytical tool with no return-shape documentation leaves some gap, so not a 5.

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 baseline is 3, but the description goes beyond the schema by enumerating the allowed group values per metric, which the schema explicitly defers to it ('see description'). This is genuinely additive meaning the schema alone does not carry.

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+resource ('Brand-level analytics') and enumerates the exact metric set, giving a precise sense of scope. It does not explicitly distinguish itself from adjacent siblings like get_campaign_stats or get_credit_usage, so it falls short of a 5.

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 metric enum and group-per-metric mapping imply when this tool is the right pick for brand reporting, but there is no explicit when-to-use guidance or named alternatives (e.g., to get campaign-specific numbers, use get_campaign_stats). Usage is inferable rather than stated.

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