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

Annotations already indicate readOnly, idempotent, and non-destructive behavior, and the description adds meaningful behavioral context: every result comes with its source and a link to the full record, and results may include contradictions and video-timestamped quotes. This goes beyond the structured annotations without contradicting 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 two sentences with no filler. The first sentence front-loads the core resource and behavior, and the second adds output guarantees and concrete use-case domains. Every clause earns its place and the structure supports quick agent scanning.

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?

With only two parameters, rich annotations, and no output schema, the description does enough by explaining what results look like: data with source and link to the full record. It could be slightly more explicit about expected output structure or no-results behavior, but the overall tool context is adequately complete for an agent to call it correctly.

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%, so the baseline is 3, but the description adds semantic guidance for the 'pregunta' parameter by listing the kinds of claims it is ideal for verifying (water, electricity, FEMA, health, budget, promises). This helps an agent formulate more useful queries than the schema alone would.

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 uses a specific verb ('Busca') and a clear resource ('el récord público verificado de Puerto Rico / PuertoRicoSinFiltros'), and lists concrete data types: primary-source data, declared-vs-delivered contradictions, and video-anchored public-hearing quotes. This clearly distinguishes it from the sibling tools, which target narrower domains like doctors, businesses, recalls, or plan directories.

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: verifying claims about water, power, FEMA, health, budget, and public promises in Puerto Rico. It does not explicitly state when not to use it or name alternative sibling tools, so it stops short of a full when/when-not guide, but the intended use case is unmistakable.

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