get_predictive_maintenance_report

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

Without annotations, the description carries full burden. It discloses that the tool calculates wear coefficients and RUL, implying a read-only, computational operation. However, it does not mention authorization, side effects, rate limits, or any computational intensity.

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?

Single sentence, efficiently conveys the core purpose without extra words. However, it could be improved by integrating parameter context without significant length increase.

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?

The tool has one required input and an output schema (not shown). The description fails to explain the input semantics or output format. Given the complexity of predictive maintenance, more detail is needed for the agent to invoke correctly.

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%. The description does not mention the only parameter (plc_id) or its role. The agent has no context on what plc_id represents or how it affects the report.

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 clearly states it 'calculates machinery wear coefficients and Remaining Useful Life (RUL) hours for preventative repairs,' which specifies the verb, resource, and outputs. It distinguishes from siblings like read_plc_registers and get_energy_consumption.

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 explicit when-to-use or when-not-to-use guidance. The context of preventative repairs is implied but no alternatives or prerequisites mentioned. The sibling tools suggest possible complementary use, but not directly stated.

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