list_measures

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

With no annotations, the description must carry the behavioral burden. It does disclose the return payload (DAX expression plus format string), which is genuinely useful, but says nothing about read-only semantics, permissions on `instance`, or whether large models produce an unwieldy response. An output schema exists, which lowers the bar slightly, but the operational profile is largely unstated.

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 tight sentences with no filler; the default scope is stated first and the narrowing condition follows. Every clause carries information.

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?

The return-value side is well covered, helped by an existing output schema. But the required `instance` argument is left unexplained and there is no note on response size or scoping for large models, which matters for an enumeration tool over an entire semantic model.

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 explains the optional `table` filter reasonably well, but the required `instance` parameter is never mentioned at all — the agent gets no clue that it must supply a model/instance identifier. One of two parameters is effectively undocumented in both schema and description.

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?

States a specific verb and resource ('List DAX measures') with explicit scope: whole model by default, or one table when `table` is supplied. It also names what each result contains (DAX expression and format string). It does not distinguish itself from the similarly-purposed sibling list_all_dax_expressions, so it falls 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?

The description implies usage through the conditional 'or for one table if `table` is given', which tells the agent how to narrow the listing. However, it offers no guidance on when to prefer this over list_all_dax_expressions, list_columns, or list_tables, and no exclusions or prerequisites are stated.

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