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

Annotations already declare readOnly, idempotent, and non-destructive behavior; on top of that, the description clarifies an important semantic: scope null means account-wide, otherwise it is one of agent_id/customer_id/agent_name. No annotation contradiction is present.

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?

A single sentence front-loads the action and result type, then packs the relevant field and scoping details into a compact clause. There is no filler or repetition beyond the necessary read-only note.

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?

For a zero-parameter, read-only listing tool with annotations covering safety, the description supplies the essential semantics of the returned policies and the meaning of null scope. An agent has enough information 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?

The tool has zero parameters, so there is nothing for the description to explain; the vacuous 100% schema coverage is sufficient. The description instead focuses on output semantics, which is appropriate for a parameterless list tool.

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 opens with a specific verb ('Return') and resource ('model-block, model-allow and token-cap policies'), and enumerates the fields returned (match mode, enforcement level, scope). This makes it immediately distinguishable from sibling list tools like spendline_list_budgets and spendline_list_providers.

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 intended use is implied: call this tool when policy details such as match mode, enforcement level, or scope are needed. However, it does not explicitly say when to prefer this over alternatives or mention any exclusions, so some inference is required.

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