natural_language_search

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

Annotations declare readOnlyHint and openWorldHint, so the description carries less burden, but it adds no behavioral context beyond the annotations. It does not describe what gets searched, result format, or any limitations, so minimal additional value is provided.

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 concise sentence that is front-loaded and contains no filler. It is appropriately sized for a simple search tool, though it is terse and could benefit from a bit more context.

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?

The description is too thin for a tool with no output schema and many sibling search tools. It fails to explain what types of data can be searched, how results are returned, or how it differs from other search offerings, leaving the agent without enough context to use it reliably.

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 schema already describes both parameters clearly (query and limit). The description adds no additional semantic meaning, 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 clearly states the tool searches ServiceNow using plain English, satisfying the verb+resource criteria. However, it does not distinguish itself from sibling search tools like nlq_query or ai_search, so it loses the differentiation point.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of exclusions, prerequisites, or preferred use cases, leaving the agent to guess based solely on the name.

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