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

Adds important behavior beyond the annotations: natural-person RUCs return found:false with reason natural_person_not_served and omit name, status, and address, while companies return specific registered fields. The annotations already cover read-only, idempotent, and non-destructive behavior, and the description is consistent with them.

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 front-loaded with the core purpose and data source, then adds eligibility rules and use cases. It is dense but every sentence carries operational 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 output schema and rich annotations, the description still supplies all necessary eligibility and edge-case behavior for correct invocation. An agent knows what the tool returns, what it excludes, and why an excluded RUC would produce found:false.

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?

The schema fully documents the single ruc parameter as an 11-digit digits-only string, but the description adds eligibility semantics tied to RUC prefixes: 20 and 00 are served, while 10, 15, and 17 are excluded. That is useful meaning beyond the schema's format guidance.

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?

States a specific verb (look up), resource (one Peruvian taxpayer by 11-digit RUC), data source (SUNAT's register), and scope (companies and organisations only). It clearly distinguishes this single-RUC lookup from broader searches and explicitly excludes natural-person RUC prefixes.

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?

Gives concrete use cases such as checking whether a RUC is real and active, KYC, counterparty checks, and resolving a RUC from an invoice. It also states a clear exclusion for natural persons, but does not name sibling pe_ruc_search as the alternative for other lookup patterns.

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