enaho_serie

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

The description goes well beyond the annotations by disclosing internal behaviors: it downloads and merges missing data reusing the cache, estimates with each year's complex design, calculates year-over-year variation, and validates the variable across waves. This provides significant context about side effects and data quality checks that annotations alone do not convey.

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 well-structured with the core action front-loaded, followed by process details, a rationale for choosing this tool, and a critical caveat about monetary values. Each sentence earns its place; it is information-dense without redundancy, appropriately sized for a complex tool.

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 tool's complexity (9 parameters, output schema available), the description is complete: it explains the workflow, the reason for its existence versus a loop, the side effects (download/cache), and a key interpretative warning. The presence of an output schema means return-value details need not be in the description.

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 high (78%) with parameter descriptions already present. The description adds global context (the same estimation is applied each year) but does not provide additional per-parameter meaning beyond what the schema already states. This aligns with the baseline 3 for high schema coverage.

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 opens with a specific verb+resource statement: 'Repite la misma estimacion en cada anio del rango y devuelve la serie.' It clearly explains the tool's core function (produce a temporal series by repeating an estimation) and explicitly contrasts it with calling enaho_estimar in a loop, distinguishing it from its closest sibling.

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 explicit guidance on when to use this tool instead of alternatives: it checks the index for variable existence and label changes, which is stated as the main reason to use it rather than looping over enaho_estimar. It also warns about monetary values requiring deflation, adding caution for interpretation.

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