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

Annotations already cover the read-only, idempotent, non-destructive safety profile, so the bar is lower, and the description adds substantial domain context: modes are 'capped by platform_mode', 'acted' counts records that changed something, one conversation can cross several bands, and usage 'null = no limit'. These semantics go well beyond the structured fields.

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 core purpose, then structured as a labeled list of returned sections (use_cases, bots, by_purpose, bands, usage). It is dense but each clause defines a distinct output section, so little is wasted; it is slightly long for a single run-on block.

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?

There is no output schema, so the description carries the burden of explaining the returned structure, and it does so section by section. Combined with the fully documented input schema, an agent has enough to interpret the response correctly.

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 the schema already documents since/until (YYYY-MM-DD, default last 30 days) and fields filtering. The description only alludes to a 'date range' and adds nothing about parameter formats, so the baseline 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?

It states a specific verb+resource: summarizing the account's AI classifications for a date range, and enumerates the exact sections returned (use_cases, bots, by_purpose, bands, usage). This is clearly distinguishable in kind from reporting siblings like get_agent_report or get_sentiment_report, but it never names or contrasts those siblings explicitly.

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 when-to-use guidance, no prerequisites, and no named alternatives among the many summary/report siblings (get_account_summary, get_agent_report, list_all_conversation_statistics). The text explains what the output contains but not the conditions under which an agent should choose this tool.

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