list_tables

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

With no annotations, the description carries the full behavioral burden. It discloses that this is a listing operation, scoped to a model, with optional text search and package filtering, and that rows are intentionally brief. This is meaningful behavioral context, though pagination semantics and the need for an open model are left implied.

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 focused sentences with no filler. The core action and scope are front-loaded, followed by search/filter capabilities, then a routing hint. Every clause earns its place without repeating schema fields.

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?

Adequate for a basic paginated list: required model_id, optional filters, and the get_table fallback are all present. With no output schema and no annotations, however, the description omits pagination details and any indication of which row fields are returned, so an agent still has to infer some invocation expectations.

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%, so the description must compensate. It adds real meaning to query ('text search over code/name') and package_ref ('package filter'), and model_id is implied by 'of a model.' It does not explain page/page_size behavior or how pagination interacts with the returned brief rows, leaving those to be inferred from names and defaults.

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 is specific and action-oriented: 'List tables (PDM) or entities (CDM/LDM) of a model' and it clearly separates itself from get_table via 'Returns brief rows - use get_table for full detail.' However, it does not differentiate from the sibling search_tables, which overlaps with the built-in 'text search over code/name' behavior, so sibling distinction is incomplete.

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 gives a concrete routing rule: if you need full detail, use get_table instead. It also tells the agent that text search and package filtering are optional capabilities of this listing tool. It stops short of explaining when search_tables would be more appropriate, so it is useful but not exhaustive.

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