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

Annotations already declare readOnly, idempotent, non-destructive, so safety is covered; the description adds genuinely useful behavioral context instead of repeating it — the window is always compared against the previous equal-length window, and topics are keyword themes from opening messages rather than a classifier, which warns the agent against over-trusting them. It does not mention pagination or result size limits beyond the schema.

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?

One dense opening sentence front-loads purpose and payload, followed by short usage and caveat sentences. It is long but nearly every clause carries distinct content (each metric named is a separate return field), so little is wasted.

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 read-only annotations and an output schema present, the description need not document return shapes, yet it still tells the agent what the analyst view contains and warns about the topic-classification caveat. The only gap is that it never positions the tool against its closest sibling for a reader choosing between them.

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%, with both `days` and `topics` fully documented including ranges and defaults, so the baseline is 3. The description reinforces the comparison-window meaning of `days` but adds no new syntax or semantics beyond what the schema already states.

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 (analyst view of this workspace's support) and then enumerates exactly what is returned: recurring topics with trend, repeated questions, volume and escalation change, AI fallback rate, CSAT/sentiment change, answer sources, and a daily volume series. That level of output enumeration makes it unmistakable against siblings like get_support_overview or list_recent_conversations.

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?

Gives concrete trigger phrases ('what are customers asking about', 'what's trending') and a cadence context (weekly/monthly support review), plus a follow-up instruction to read examples with fetch before concluding. It stops short of stating when to prefer a sibling like get_support_overview or list_unanswered_questions instead, so no explicit exclusion is given.

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