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Listar tableros de indicadores del SUT

list_sut_indicadores
Read-only

Lists available Ministry of Labor SUT indicators from Power BI dashboards, covering contracts since 2015, labor demand, and gender policy for further querying.

Instructions

Ministerio del Trabajo SUT Power BI dashboards (contracts since 2015 by industry/province/gender, labor demand, gender policy). Next: get_sut_indicador_schema, then query_sut_indicador.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNotext summary (default) or json structured result.text

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.10.0
    • addedInput schema / properties / format / description
      Added value: +"text summary (default) or json structured result."
  2. Changed3 schema fields changedv0.8.14
    • removedInput schema / properties / format / title
      Removed value: -"Format"
    • removedInput schema / title
      Removed value: -"list_sut_indicadoresArguments"
    • removedOutput schema / title
      Removed value: -"list_sut_indicadoresDictOutput"
  3. First observedv0.8.12

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description adds the domain scope of the underlying dashboards, which is useful context, but says nothing about pagination, rate limits, or freshness of the referenced dashboards beyond what is already structured.

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

Conciseness4/5

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

It is a compact two-part statement that front-loads the resource scope before the workflow hint, with no filler. The parenthetical dimension list is dense but each element is informative, so nothing is wasted.

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, return-value explanation is not required, and the description supplies the subject matter plus the chained next-tool sequence. It is essentially complete for a low-parameter read-only list tool, with only minor gaps around result size or freshness.

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?

There is a single 'format' parameter with 100% schema description coverage and an enum, so the schema already fully explains it. The description adds no format-specific semantics, so the schema does the heavy lifting and the baseline of 3 applies.

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?

The description names a specific resource (Ministerio del Trabajo SUT Power BI dashboards) and enumerates the content dimensions (contracts since 2015 by industry/province/gender, labor demand, gender policy), which distinguishes it from other government-data siblings like get_sipa_resumen_indicadores or the BCE indicator tools. The listing verb is only implied by the name rather than stated in the description, so it is clear but not maximally explicit.

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 gives an explicit workflow: 'Next: get_sut_indicador_schema, then query_sut_indicador,' routing the agent to the correct follow-on tools. It does not state a when-not-to-use condition or contrast directly with alternative list_* tools, so it stops just short of full alternative guidance.

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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