natural_query

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

No annotations are provided, so the description carries full burden. It only states it processes queries and returns structured data, but does not disclose side effects, idempotency, rate limits, or behavior for ambiguous queries. This is insufficient for a tool that accepts free-form natural language.

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 two sentences with no filler. It efficiently conveys the tool's purpose and parameter usage. Every sentence adds value.

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?

Given the simple input schema (2 params) and no output schema, the description is fairly complete. It explains what the tool does and the parameters. However, it could mention the return format (e.g., JSON) or potential limitations, making it slightly incomplete.

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% and includes examples. The description adds some context (e.g., listing entity types) but largely overlaps with the schema's parameter descriptions. Baseline 3 is appropriate as the description does not significantly enhance understanding beyond the schema.

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 executes natural language queries against Ambivo entity data, specifying supported entities like leads, contacts, opportunities. It is specific and distinguishes from the sibling tool 'set_auth_token' which handles authentication.

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 implies usage (for querying entity data) but does not provide explicit guidance on when to use versus alternatives, nor does it mention when not to use it. Since there is only one sibling (auth token), the context is limited but could benefit from clarification.

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