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List Explainers

list_explainers
Read-onlyIdempotent

Dapper's own curated explainers: what a thing is, in prose, written by the editorial team — «El espectro radioeléctrico», «Ciberseguridad», «Internet de las cosas», industry associations.

For definition questions: when a piece exists it is sourced and dated. Coverage is Colombian and sectoral, so legislative procedure is not covered here: quorum, majorities and deadlines have no piece and no table behind them.

The list carries the summary; fetch one by id for the body.

Input Schema

NameRequiredDescriptionDefault
qNoMatch on title and summary, every token in any order: «espectro», «datos personales».
limitNoPieces per page (1-100).
country_idNoDeprecated alias: comma-separated numeric ids, e.g. 8,2,6.
country_codeNoComma-separated country codes, e.g. BR,CO,CL.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real substance beyond that: coverage is Colombian and sectoral only, pieces are sourced and dated when they exist, and the list returns summaries rather than bodies. Return field details are left to the output schema.

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?

Front-loads what the resource is, then usage, then the coverage caveat, then the follow-up path in four tight sentences. Every sentence carries information, though the examples and the quorum/majorities enumeration are slightly heavier than needed.

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?

With an output schema and full annotation coverage in place, the description supplies exactly the missing pieces: the domain boundary of the content, the fact that the list is summary-only, and the id-based path to the full body. Nothing an agent needs to call this correctly is absent.

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%, with q, limit, country_id (marked deprecated) and country_code each documented in the schema itself. The description adds no parameter-level detail — the mention of 'summary' and 'id' is about returned data, not inputs — so the baseline of 3 applies.

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?

States a specific verb and resource ('Dapper's own curated explainers ... written by the editorial team') with concrete examples of the content type. It also distinguishes itself from the sibling get_explainer by noting that the list carries only the summary and the body requires fetching by id.

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?

Gives an explicit trigger ('For definition questions') and an explicit exclusion ('legislative procedure is not covered here: quorum, majorities and deadlines have no piece'), which steers an agent away from a dead end. It stops short of naming the alternative tool (get_legislative_process) that should be used instead, leaving that inference to the agent.

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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