indec_describe_datasetReturns a dataset’s columns with exact names, types, meanings, pagination sort key, and frequency so you can inspect its structure before building filters.
Devuelve las columnas (nombre exacto, tipo y significado), la clave de orden para paginar y la frecuencia de un dataset. Usalo antes de armar filtros con indec_query_dataset. No requiere token.
| Name | Required | Description | Default |
|---|---|---|---|
| dataset | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds value beyond them by stating 'No requiere token', which tells the agent no authentication step is needed before calling. It stops short of describing response shape or error behavior, which keeps it at a 4 rather than a 5.
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?
Two sentences, front-loaded with the return contents and followed by the routing instruction. Every clause carries information: what comes back, when to call it, and that no token is required.
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 no output schema, the description correctly takes on the burden of explaining return values and does so concretely (columns, ordering key, frequency). For a one-parameter enum tool this is nearly sufficient; only the response structure and error handling for an invalid dataset are left unstated, a minor gap.
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 0%, so the description would normally have to carry the parameter meaning. It only says the tool operates 'de un dataset', adding minimal semantics beyond the parameter name; however, the single parameter is a fully enumerated list of 19 dataset identifiers, which is largely self-documenting. Baseline 3 is appropriate given the enum does most of the work.
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 states a specific verb (devuelve) and enumerates exactly what is returned: column names with type and meaning, the sort key for pagination, and the dataset frequency. It is immediately distinguishable from siblings like indec_query_dataset or indec_list_datasets because it is the schema/metadata inspection tool.
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?
It gives an explicit sequencing rule: call this before building filters with indec_query_dataset, naming the concrete alternative it complements. That is a real when-to-use instruction rather than an implied one, and it leaves little room for the agent to pick the wrong sibling first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.