model_summary

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

Annotations already cover read-only, idempotent, closed-world behavior, and the description adds a genuinely non-obvious trait: partial failure is tolerated, with per-table errors reported while remaining counts still return. It does not address what happens if the model itself cannot be read or whether counts are cached/live.

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?

Two short sentences, front-loaded with the returned content, with no filler. The mid-sentence line break is a minor formatting wart but nothing is wasted.

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 output schema, the description does the right thing by enumerating returned fields and the partial-error shape. However, for a tool with a required enum argument, leaving that argument entirely unexplained is a meaningful completeness gap.

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% and the single required parameter 'product' (enum gen/civil) carries no explanation in the schema. The description never mentions 'product' at all, so it does not compensate for the gap — an agent must guess that it selects which product's model to summarize.

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 concrete resource and scope: record counts for specific tables (nodes, elements, materials, sections, thicknesses, static load cases) plus the unit system. That is far more specific than the name alone. It does not explicitly contrast itself with siblings such as read_model_info, list_tables, or read_table, so it stops short of a 5.

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 statement of when to use this versus read_model_info, list_tables, or read_table, and no prerequisites (e.g., that a model must be open). Usage is only implied by the fact that it returns an overview.

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