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

No annotations are provided, so the description carries the full behavioral burden. It discloses useful non-obvious traits: returns up to 10 matches, empty results do not consume a credit, and successful matches count toward the shared 5-lookup MCP trial. It does not describe response field shapes or failure modes, but for a simple lookup tool this is adequate.

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 compact sentences, each earning its place. The first sentence front-loads the operation and endpoint, while the next two add only non-obvious behavior around match limits and quota consumption. There is no filler or redundant restating of the schema.

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 single-parameter lookup with no output schema and no annotations, the description adequately covers input, expected result count, and credit/trial behavior. It stops short of describing the exact shape of a match or explicitly routing to sibling tools, but those are minor gaps for successful 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?

Schema coverage is 100%, and the query parameter is already described as a legal or DBA name fragment with length constraints. The description reinforces that this is a name search against the FMCSA endpoint but does not add new parameter-level details such as formatting, wildcard behavior, or normalization rules. Baseline 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 clearly identifies a specific verb and resource: searching carrier legal or DBA names via the FMCSA census name endpoint. It also states that it returns up to 10 matches, which helps distinguish it from identifier-based lookups like lookup_dot and lookup_mc, though it does not explicitly name those siblings.

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 gives clear context for when to use the tool: when searching by legal or DBA name fragment. It also communicates the no-credit-on-empty-results behavior and the trial quota usage. However, it does not explicitly state when not to use it or steer the agent toward lookup_dot/lookup_mc for DOT/MC number lookups.

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