consultar_ruc

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

No annotations exist, so the description carries full burden. It discloses the local nature and index prerequisite, but does not mention error handling, rate limits, or behavior for missing RUCs.

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 concise sentences. The first front-loads the primary purpose and returned data, the second gives a prerequisite, and the third clarifies privacy. No redundant or irrelevant 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 simple one-parameter tool with no output schema, the description covers purpose, prerequisite, and local operation. It lacks details on error responses or index requirements, but is sufficient for basic usage.

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?

Only one parameter (ruc) with schema description coverage 0%. The description implicitly defines it as a RUC number, adding minimal value beyond the tool name. No format or constraints are specified.

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 consults a RUC locally and lists returned fields (razon social, estado, etc.). The verb 'consultar' and resource 'RUC' are specific. However, it does not explicitly differentiate from siblings like validar_ruc or buscar_razon_social.

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 provides a prerequisite (building index with ingest.py) and notes the query is local. But it lacks explicit guidance on when to use this tool versus alternatives or when not to use it.

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