churn_by_segment

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

No annotations are supplied, so the description carries the full behavioral burden, and it discloses almost nothing: not that this is a read-only aggregation, not what the accumulation window is, and not what the default as_of=null means. The only behavioral hint is the diagnostic framing, which is weak for a tool with zero annotation coverage.

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 with the metric first and the purpose after the dash; nothing is wasted. It is arguably too terse for the gaps it leaves, but the structure itself is clean.

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?

An output schema exists, so return values need not be described, and the segment dimension is covered. The unresolved as_of semantics and the absence of any behavioral disclosure leave a real gap for a two-parameter analytics tool.

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 0%, so the description must compensate. It does clarify the meaning of the segment values (plan, city, sales channel), which is useful, but the as_of parameter is left entirely unexplained — no format, no default-null semantics, no timezone or cutoff behavior.

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?

The description names a specific metric (accumulated churn) and the three segmentation dimensions (plan, city, sales channel), which map exactly to the enum in the schema. It implicitly distinguishes itself from time-series siblings like churn_by_month and churn_reasons, though it never names 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 clause 'para achar onde o problema se concentra' gives a diagnostic use case, which is more than nothing. But there is no explicit when-to-use versus churn_by_month, churn_reasons, or churn_risk, and no stated prerequisites or exclusions.

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