Location trends

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

Annotations already cover read-only/idempotent/non-destructive behavior; the description adds meaningful runtime behavior by disclosing that weekly rows carry partial_week=true when the date range cuts into a week. It does not fully describe output shape, but this is a strong addition beyond the annotations.

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?

Three sentences, no filler. The core purpose is front-loaded, the use case follows, and the partial_week edge case earns its place as the final sentence.

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 conveys the return concept (late rate/no-shows per site by grouping) and a key edge-case flag. It is sufficient for an agent to invoke correctly, though it leaves minor output formatting details unspecified.

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 80%, and the schema already explains to/from/location/grace_minutes with defaults and constraints. The description adds only light context for group_by via 'grouped by weekday or by week', which is consistent with the schema enum, so a baseline 3 is appropriate.

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 opens with a specific, scoped statement — 'Late rate and no-shows per site, grouped by weekday or by week' — naming the resource and aggregation. The phrase 'site-level patterns' clearly separates it from event-level siblings like find_late_arrivals and employee_attendance.

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?

'Use to spot site-level patterns such as a bad day of the week' gives an explicit use case. It does not mention when not to use it or name alternatives, so it falls short of a 5 but is clearly contextualized.

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