generate_model_summary

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It only mentions a 'high-level summary' without stating that this is a read-only operation, how it aggregates counts, or any caveats about performance or data freshness. This is insufficient for a tool that likely queries the entire model.

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, tightly written sentence with no redundant words. It is front-loaded with the core action. However, it is so brief that it borders on under-specification, though it earns a 4 for structure and economy.

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?

Despite having an output schema (which reduces the need to describe return values), the description is vague about what 'coverage' means and what counts are included. Given the existence of dedicated coverage-check tools, an agent would benefit from a note about scope (e.g., element types, diagram coverage, requirement coverage). The lack of this context makes the tool's behavior ambiguous.

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?

The tool has zero parameters and the schema coverage is 100% (empty schema), so there is nothing to explain. The description does not need to add parameter meaning since none exist; the baseline of 4 is appropriate.

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 returns a high-level summary of model element counts and coverage. It uses a specific verb and resource, and the intent is understandable. However, it does not differentiate itself from the sibling tool get_model_metrics, which likely serves a similar purpose, so it misses the opportunity to distinguish itself.

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 is provided on when to use this tool versus alternatives such as get_model_metrics or the specific coverage-check tools (check_requirement_coverage, check_documentation_coverage). The description offers no context on selection criteria, leaving the agent to guess which tool is appropriate.

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