delinquency_by_month

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

No annotations are supplied, so the description carries the full disclosure burden. It states the metric but says nothing about scope (all customers? a segment?), the default window (the schema's months=12 is never acknowledged), whether results are cumulative or bucketed, or how the as_of cutoff affects counting. For an analytics tool with zero annotation coverage this is thin, though the read-only nature is implicitly clear from the phrasing.

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 no filler; the metric definition arrives immediately. It is efficient rather than padded, though its brevity edges toward under-specification rather than crispness.

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 explained. But for a two-parameter analytics tool with no annotations and no parameter descriptions, the definition leaves the agent guessing about the time window and evaluation cutoff, which materially affect the numbers returned.

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 both parameters are undocumented in the schema and the description does not compensate. 'Por mês de vencimento' hints that grouping is by due date, which is useful, but as_of (what point in time delinquency is evaluated) and months (lookback window) get no explanation at all.

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 concrete metric: counting invoices per due-date month that were paid late or remain open. That is more specific than restating the name, since it defines what 'delinquency' means here (paid late OR still open). It does not distinguish itself from close siblings like delinquency_aging or delinquent_customers, which is a real gap given the crowded sibling list.

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 whatsoever: no statement of what question this answers versus delinquency_aging, delinquent_customers, or overview. An agent must infer the choice purely from the name. No prerequisites, no exclusions.

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