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

Beyond the readOnlyHint annotation, the description discloses matching behavior (exact/prefix vs nearMiss) and the required user-confirmation workflow ('only file as new if they confirm', 'ask the user'). This prevents an agent from auto-resolving or auto-creating records. It does not contradict the read-only annotation because 'file as new' is framed as a downstream decision, not a write performed by this tool.

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?

Three sentences: first sets purpose and possible statuses, second details the nearMiss rule including the confirmation requirement, third is a clear imperative ('Never guess among candidates'). Information is front-loaded and no sentence is filler.

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 one-parameter, no-output-schema tool with readOnlyHint=true, the description covers the call's purpose, parameter, returned status categories (resolved/ambiguous/none with id/candidates), and disambiguation behavior. The only minor gap is an explicit action for the 'none' status, but the overall guidance is sufficient for correct invocation.

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?

With 0% schema coverage, the description compensates by identifying the sole parameter as a 'supplier / vendor name' for a bill draft and clarifying how it is matched (exact/prefix, nearMiss). It adds semantic context beyond the raw string field. It doesn't specify formatting or case rules, but for a single string this is sufficient.

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 'Resolve a supplier / vendor name for a bill draft against this company's real vendors' – a specific verb, object, and target dataset. It also lists the three outcome statuses, making the operation's scope concrete. It doesn't explicitly contrast with resolve_customer/resolve_product, but the vendor-specific wording is enough to identify the intended tool.

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?

Gives clear context: the tool is for bill-draft vendor names matched against real vendors, and instructs to 'ask the user' whenever candidates are ambiguous or nearMiss. It explicitly says 'Never guess among candidates,' which is a strong usage rule. It doesn't name alternative sibling tools for exclusion, so no direct when-not-to-use statement.

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