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Ine Es

by io.github.pipeworx-io
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Table Data

table_data
Read-onlyIdempotent

Fetch data points for ALL series in an INE table at once. Use nult=N for the last N periods, or date="YYYYMMDD:" for everything from that date on (trailing colon = open-ended range). Each series object carries a Data[] array of {Fecha (epoch ms), Anyo, Valor}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate filter, e.g. "20250101:" for from Jan 2025 onward.
langNoResponse language. Default EN.
nultNoReturn the last N periods (e.g. 1, 12).
tableIdYesNumeric table Id, e.g. "50902".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "nult": 12,
+    "tableId": "50902"
+  },
+  {
+    "date": "20250101:",
+    "lang": "EN",
+    "tableId": "50902"
+  }
+]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, non-destructive. The description adds output structure (Data array with Fecha, Anyo, Valor) which is valuable since no output schema exists.

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, front-loaded with purpose, no fluff. Every sentence contributes essential information.

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

Completeness5/5

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

Given no output schema, the description sufficiently covers purpose, parameter usage, and output format. Additional details like date format trailing colon are included.

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

Parameters4/5

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

Schema coverage is 100%, baseline 3. The description adds examples (nult=12, date=...) and implies mutual exclusivity between nult and date, adding value beyond schema descriptions.

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 fetches data points for ALL series in an INE table at once, using a specific verb and resource. It distinguishes from siblings like series_data (likely per-series) and series_in_table.

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?

The description explains how to use parameters (nult=N for last N periods, date=...), providing clear usage patterns. It lacks explicit when-not-to-use or alternative tool mentions, but the context is implied.

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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