machine_oee

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

Annotations already declare readOnlyHint=true, so safety is covered. The description still adds genuine behavioral context beyond that: the OEE formula for interpreting the number, and the non-obvious ordering rule that results are sorted worst first by machine. It does not disclose default date-range behavior when date_from/date_to are omitted.

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?

Two tightly written sentences with no filler; the metric definition and grouping are front-loaded before the result-ordering note. Efficient, though the parenthetical formula is the only elaboration offered.

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 an output schema present, return values need not be explained, and the description covers metric meaning, grouping grain, and result ordering. The main gap is the behavior when all filter parameters are left at their null defaults (e.g., what time window is assumed).

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%, so the schema already documents line, date_from, date_to, and machine_id formats. The description only echoes the group_by options and the date scoping ('for a period'), adding no syntax or default details beyond the schema. Baseline 3 applies.

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 the specific metric (OEE, with its formula spelled out as availability x performance x quality) and the resource scope, plus the grouping dimension. An agent knows exactly what is computed and at what grain, though it never distinguishes itself from siblings like production_kpis or downtime_pareto.

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?

No when-to-use guidance is given. The description never says to prefer this over production_kpis (general KPIs) or downtime_pareto (loss breakdown), nor when each group_by choice is appropriate. Usage is only inferable from the metric name.

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