Diagnose site faults

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

With no annotations, the description fully carries the behavioral burden. It reveals the comparison logic, the weather-control mechanism (irradiance), and the three mutually exclusive diagnoses (dead inverter, reporting gap, bad weather). This is rich, actionable context far beyond a typical one-liner.

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 with zero fluff. The methodology is front-loaded, followed by the fault distinctions, then the practical usage examples. Every sentence contributes to the agent's understanding.

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 description covers the core algorithm and use cases, which is the essential knowledge for calling this diagnostic tool. However, with no output schema present, it does not explicitly state what the tool returns or mention any prerequisites beyond the parameters. The missing return format is a minor gap.

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 coverage is 100% with clear parameter descriptions (nodeId, inclusive/exclusive dates, aggregation enum). The description only references 'a date range' and does not add semantic meaning beyond the schema, so the 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?

The description uses a specific verb ('Diagnose') with a precise resource ('solar site') and method ('comparing each inverter against its own siblings, with irradiance as the weather control'). It further enumerates three distinct fault outcomes, clearly differentiating it from generic tools like get_anomalies or compare_fleet.

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 description provides explicit when-to-use scenarios: 'is anything wrong at this site', 'which inverter is broken', or 'why did output drop'. It does not, however, name alternatives or state when not to use the tool, so it stops short of a full 5.

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