scrap_summary

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

Annotations already declare readOnlyHint=true, so the safety profile is covered and the description only needs to add aggregation context, which it does by naming the grouping dimensions. It does not disclose the effect of omitted date bounds (both default to null) or the default grouping, so a mutation-free but behaviorally thin addition.

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 compact sentence with the metric front-loaded and the grouping options trailing. No filler, though it is a verbless fragment rather than a fully formed instruction.

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. For a 3-parameter read-only aggregation with an enum and documented date patterns, the description is nearly sufficient; only the null date defaults and default grouping are left unstated.

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 67% and both date parameters are documented with ISO format in the schema itself. The description restates the group_by enum values, which is largely redundant with the structured enum, and adds no explanation of default behavior or how grouping changes the returned rows. 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?

States a specific resource (scrap quantity and scrap rate) and the dimensions over which it aggregates (reason, machine, product), which is enough to separate it from siblings like machine_oee and downtime_pareto. It never names an alternative tool, but the resource is precise and unambiguous.

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 phrase 'for a period' and the list of grouping options imply the usage context, but there is no explicit when-to-use/when-not guidance and no mention of how this differs from other analytics siblings such as production_kpis. Usage is left to inference.

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