Entity Statistics

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

Annotations already declare readOnlyHint=true. Description adds that counts are sorted and output structure. No contradictions, but lacks disclosure of boundary conditions (e.g., behavior with empty drawings or performance).

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, front-loaded with main action and output structure. The marketing sentence is slightly extraneous but not harmful. Efficient overall.

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?

With no parameters and an output schema, the description explains output format. However, it assumes knowledge of entity types and layer names; no mention of scope (all entities? visible only?). Still, fairly complete for a simple analysis tool.

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?

No parameters, schema coverage 100% trivially. Description adds no parameter info, but baseline 3 is appropriate as schema already covers parameters.

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?

Clearly states it analyzes the drawing and returns entity counts grouped by type and layer, specifying the return structure. Sibling tools like analysis_layer_stats and analysis_select_by_type are differentiated by combining both groupings.

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 guidance on when to use this tool over alternatives. Despite marketing claim, it doesn't explain context or prerequisites. Missing explicit when-to-use or when-not-to-use information.

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