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huggingface_search_dataset

Search the official Chilean legal doctrine dataset on Hugging Face and retrieve contextual results with direct links to official citations.

Instructions

Consulta el repositorio público oficial en Hugging Face Datasets Hub (pablobenavidesj/doctrina-jurisprudencia-chile) y recupera contexto y enlaces directos con citas oficiales.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNúmero máximo de archivos o recursos a devolver (por defecto 5)
queryYesTérmino de búsqueda doctrinal o institucional (ej. 'responsabilidad', 'despido', 'contratos')

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.6.5

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states that it retrieves context and direct links, but does not mention error handling, rate limits, pagination, or whether it is read-only. The description offers minimal behavioral context beyond the basic action.

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?

The description is a single, front-loaded sentence that clearly identifies the resource and action. It is concise and avoids redundancy, though it could be structured into separate sentences for action and output to improve readability.

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

Completeness3/5

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

The tool is simple with 2 parameters fully documented in the schema. No output schema exists, so the description should clarify the return format. It mentions context and direct links but does not specify the structure or edge cases (e.g., empty results). It is adequate but could be more explicit about what is returned.

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?

Both parameters have schema descriptions (limit and query) with examples, so schema coverage is 100%. The description does not add extra meaning beyond what the schema provides; it does not elaborate on how the query is used or how limit affects the results. Baseline 3 applies since the schema carries the semantic load.

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 clearly states the action (consult/retrieve) and the specific resource (Hugging Face dataset pablobenavidesj/doctrina-jurisprudencia-chile). It mentions the output (context and direct links with official citations), giving a clear purpose. It does not explicitly contrast with sibling search tools, but the unique dataset reference helps differentiate it.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternative search tools like cgr_search_jurisprudencia or dt_search_doctrina. It does not mention any exclusions, prerequisites, or conditions that would help an agent select it over siblings.

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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