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

The annotations already declare this as a safe, read-only, idempotent, non-destructive operation. The description adds important behavioral guidance by warning that similarity scores and is_auto_match are only hints and do not verify selection, owner authority, or financial eligibility, which is valuable context beyond the annotations.

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 three tight sentences, front-loading the purpose and following with the ambiguous-case handling and an important caveat. Every sentence earns its place with no redundant or filler text.

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 low-complexity, read-only suggestion tool with full schema coverage and no output schema, the description is complete enough. It explains the matching behavior, ambiguity handling, and the meaning of key output hints like similarity scores and is_auto_match.

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 100%, so both the query and limit parameters are already documented with examples, constraints, and defaults. The description does not add parameter-specific semantics beyond the schema, so the baseline score of 3 is appropriate.

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 uses a specific verb and resource: 'Find possible address matches in county records' from a partial query or misspelling. It clearly identifies the task and scope, and no sibling tool in the list appears to perform address suggestion, so the agent can distinguish it without opening the schema.

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 clear usage context: use for partial queries or misspellings, and if the property is ambiguous, ask the user to choose before drawing conclusions or taking action. It does not name alternatives or explicit exclusions, but there are no obvious sibling alternatives for this specific suggestion task.

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