diagnose_drops

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool's action (run diagnostic battery) and output format (drop sources by layer, bottleneck classification, leading indicators), which adds value beyond the input schema. However, it doesn't disclose potential side effects, execution time, permission requirements, or error conditions, leaving gaps for a diagnostic tool.

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?

The description is efficiently structured in two sentences: the first states the action and purpose, the second specifies the return format. Every element earns its place with no redundant information, making it appropriately sized and front-loaded for quick comprehension.

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?

Given the tool's complexity (diagnostic analysis with multiple output components), no annotations, and no output schema, the description does well by explaining what the tool does and what it returns. However, it could be more complete by mentioning execution characteristics or error handling. The absence of an output schema means the description must cover return values, which it does adequately but not exhaustively.

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 100%, so the schema already documents all three parameters (sensor, from, to) with their types and formats. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 where the schema does the heavy lifting.

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 the tool's purpose with specific verbs ('run a comprehensive diagnostic battery') and resource ('against a sensor'), and distinguishes it from siblings by focusing on drop diagnosis rather than monitoring, querying, or testing functions. It specifies what the tool does (identify where drops occur and why) and what it returns (drop sources by layer, bottleneck classification, leading indicators).

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 implies usage context (when drops need investigation on a sensor) but doesn't explicitly state when to use this tool versus alternatives like 'sensor_status', 'sensor_performance_verdict', or 'query_sensor_metric'. It suggests a comprehensive diagnostic approach but lacks explicit guidance on prerequisites or exclusions.

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