robot_measure

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

No annotations are provided, so the description carries full burden. It reveals that metrics are computed but does not state if the tool is read-only, whether it requires a reasoner for certain sets, or any potential side effects. This is adequate but could be more transparent.

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 short and front-loaded with the main purpose. The list of metric sets and output formats is concise and well-structured, with no unnecessary words.

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 has 13 parameters, no schema descriptions, and no annotations, the description is too minimal. It covers only the core metrics and format, leaving many important parameters unexplained. The existence of an output schema does not compensate for missing parameter details.

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?

With 0% schema description coverage, the description only explains 'metrics' and 'format' parameters. The other 11 parameters (input, output, working_directory, etc.) are undocumented in both schema and description, leaving a significant gap.

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 computes ontology metrics (entity counts, axiom counts, complexity). This is a specific verb+resource, and the tool is distinct from siblings like robot_query or robot_reason.

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?

It lists metric sets (essential, extended, etc.) and output formats, guiding when to use different configurations. However, it does not explicitly contrast with sibling tools or provide conditions for using this tool over others.

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