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Ibge Br

by io.github.pipeworx-io
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List Aggregates

list_aggregates
Read-onlyIdempotent

Browse the catalog of IBGE/SIDRA aggregate tables grouped by subject (inflation, agriculture, demographics, etc.). Use to discover aggregate ids to pass to aggregated_data. Optionally filter by research/subject acronym.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "acronym": "IPCA"
    },
    "name": "list_aggregates"
  }
}

Input Schema

NameRequiredDescriptionDefault
acronymNoOptional research acronym to filter by, e.g. "PNAD", "IPCA". Omit to list everything.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "acronym": "IPCA"
+  },
+  {
+    "acronym": "PNAD"
+  }
+]
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, openWorldHint, and destructiveHint, so the agent knows it's safe. The description adds that results are grouped by subject and allows discovery, but doesn't add significant behavioral details like pagination or output format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words, purpose front-loaded. Highly concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple browse/discovery tool with one parameter and full annotation coverage, the description adequately covers purpose, usage, and outcome (discovering IDs). Lacks output structure details but functional given context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with the acronym parameter description. The description restates that it's optional and for filtering, adding no new semantic meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool browses a catalog of IBGE/SIDRA aggregate tables grouped by subject, with the purpose of discovering aggregate IDs to pass to aggregated_data. This distinguishes it from the sibling aggregated_data tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states use case: discover aggregate IDs for aggregated_data. Also mentions optional filtering by acronym. While not exhaustive about when not to use, the guidance is clear and sufficient for this role.

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

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