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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Evaluate a query' weakly implies a read-only analysis, but the description does not state whether the plan is mutated, whether results are returned, or what side effects occur. This is a meaningful transparency gap for a tool with no annotation safety profile.

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, front-loaded sentence with no filler. Every part earns its place: the verb, the target resource, and two clarifying examples that make the purpose concrete.

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?

Although an output schema exists, this is a 4-parameter tool with no annotations, no enum values, and 0% schema description coverage. The description explains the high-level intent but omits parameter semantics, usage boundaries, and distinctions from closely related cognitive tools, so an agent is not fully equipped to invoke it correctly.

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 for the four otherwise unexplained parameters. The 'What if capacity drops?' examples hint at how query_type and parameters might be used, but the description never explains required fields like task_structure_id, optional plan_id, or the expected shape of parameters. It adds conceptual value but not enough parametric guidance.

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 begins with a specific verb and resource: 'Evaluate a counterfactual query on a plan', and gives concrete examples ('What if capacity drops?', 'What if a route fails?') that make the operation identifiable. It does not, however, distinguish itself from sibling tools like cognitive.counterfactual_what_if or cognitive.plan_with_counterfactuals, so it stops short of strong differentiation.

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 phrase 'on a plan' and the example counterfactual questions imply when the tool is appropriate, but there is no explicit when-to-use, when-not-to-use, or mention of alternative sibling tools. An agent must infer usage from the examples rather than being directed to the right tool.

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