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Open Economics

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Query Federal Public Debt statistics

get_tesouro_dpf
Read-onlyIdempotent

Retrieve one official monthly RMD table at a time: debt composition, DPMFi holders, average maturity, average maturity by indexer, monthly cost, or twelve-month cost. Units remain table-specific and are never combined.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoInclusive last month, YYYY-MM.
fromNoInclusive first month, YYYY-MM.
limitNoMaximum debt-statistics rows to return.
queryNoCategory-label search; useful when category IDs are unknown.
tableNoVersioned RMD table to retrieve.composition
categoriesNoExact category IDs returned for the selected table by get_tesouro_dpf_schema.
dataset_idYesThe official Tesouro Nacional DPF debt-profile dataset identifier.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesSource-preserving data or schema payload for the selected official dataset.
metaYesResponse metadata and source provenance.
linksNoRelated API links.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • addedInput schema / properties / dataset_id / description
      Added value: +"The official Tesouro Nacional DPF debt-profile dataset identifier."
    • addedInput schema / properties / from / description
      Added value: +"Inclusive first month, YYYY-MM."
    • addedInput schema / properties / limit / description
      Added value: +"Maximum debt-statistics rows to return."
    • addedInput schema / properties / table / description
      Added value: +"Versioned RMD table to retrieve."
    • addedInput schema / properties / to / description
      Added value: +"Inclusive last month, YYYY-MM."
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "description": "REST-aligned Open Economics response with data, metadata, links, and source provenance.",
+  "properties": {
+    "data": {
+      "description": "Source-preserving data or schema payload for the selected official dataset."
+    },
+    "links": {
+      "additionalProperties": {},
+      "description": "Related API links.",
+      "properties": {
+        "observations": {
+          "description": "Canonical observations endpoint for this dataset.",
+          "type": "string"
+        },
+        "self": {
+          "description": "Canonical URL for this response.",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "meta": {
+      "additionalProperties": {},
+      "description": "Response metadata and source provenance.",
+      "properties": {
+        "dataset": {
+          "description": "Open Economics dataset identity when supplied."
+        },
+        "provenance": {
+          "description": "Upstream source URLs, versions, timestamps, and methodology details."
+        }
+      },
+      "type": "object"
+    }
+  },
+  "required": [
+    "data",
+    "meta"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

Does 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 genuine behavioral context beyond that: results are per-table, one table per call, and units are table-specific and must not be aggregated across tables.

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 that are fully front-loaded: the retrieval scope comes first, then the critical units caveat. Every clause carries informational weight with no filler.

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?

With an output schema present, a fully documented 7-parameter schema, and complete annotations, the description need only convey scope and the table-isolation rule, which it does. The only gap is the missing pointer to the sibling schema tool for discovering category IDs.

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 description coverage is 100%, so the baseline is 3; every parameter (from/to, limit, query, table, categories, dataset_id) is documented in the schema itself. The description adds only the table-level scoping constraint, not format or semantic detail beyond the schema.

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

Purpose4/5

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

States a specific verb (Retrieve) and resource (official monthly RMD table), and enumerates the six concrete table variants the agent can request. However, it does not explicitly name its closest sibling get_tesouro_dpf_schema, which the parameter schema relies on for category IDs, so sibling differentiation is only implied.

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

Usage Guidelines3/5

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

"Retrieve one ... table at a time" and "units ... are never combined" convey an important usage constraint, but the description never says when to call this versus get_tesouro_dpf_schema (to discover categories) or when to prefer a different dataset tool. Usage is implied rather than spelled out.

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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