measure_area

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

No annotations are provided, so the description bears full behavioral disclosure. It implies a read-only measurement operation, but does not state supported entity types, units, coordinate assumptions, output format, or any permission/behavior details beyond the basic purpose.

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 a single front-loaded sentence with no filler. It is concise, though arguably too terse for a tool with two undocumented input parameters.

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 no annotations, no output schema, and 0% schema description coverage, the description is not complete enough. It omits parameter relationships, expected return values, supported entity types, and usage context needed to invoke the tool confidently.

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% for two parameters. The description mentions 'from an entity,' which loosely maps to entity_id, but it does not explain the points array, whether the two inputs are alternatives, or what input shapes are required.

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 states a specific verb ('Measure') and resource ('planar area') and names the input source ('from an entity'). It distinguishes the tool from volume, surface-area, perimeter, and angle measurement siblings, though it does not differentiate it from polygon-area or section-area tools.

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?

There is no guidance on when to use this tool versus alternatives such as measure_polygon_area_stats or compute_section_area. The phrase 'from an entity' implies a supported input context, but no explicit when-to-use or when-not-to-use guidance is provided.

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