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agent_run

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Runs a specialized Chilean legal agent to resolve complex legal tasks by autonomously coordinating forensic research tools in offline deterministic or LLM mode.

Instructions

Ejecuta un agente jurídico especializado (ej. 'litigios', 'inmobiliario', 'probidad', 'laboral', 'dogmatico', 'forense', 'vigilante', 'clinica', 'regulatorio') para resolver un objetivo legal complejo coordinando autónomamente las herramientas de la suite en modo determinista soberano o LLM.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoModo de ejecución: 'auto' (detecta automáticamente), 'deterministic' (100% offline soberano) o 'llm'auto
taskYesMisión, objetivo o consulta legal detallada para el agente
contextNoParámetros de contexto adicionales opcionales (ej. tribunal, fojas, cbr, fechas, hechos)
agent_nameYesNombre o alias del agente a ejecutar (ej. 'litigios', 'inmobiliario', 'probidad', 'laboral', 'dogmatico', 'forense', 'vigilante', 'clinica', 'regulatorio')

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.11

TDQS

B3.3/5.0
Behavior3/5

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

Adds real context beyond annotations: autonomous coordination of suite tools and a 'determinista soberano' offline mode versus LLM mode. However, it does not disclose latency, cost, whether delegated tools can mutate state, or what the run returns — notable gaps for an orchestrator, and there is mild tension between 'autonomously coordinating tools' and readOnlyHint=true.

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?

A single front-loaded sentence with the verb leading, no filler or repetition. It is dense — the alias list and mode clause pack a lot in — but every element earns its place.

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

Completeness2/5

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

For an open-world orchestrator with no output schema and a nested context object, the description is thin: no indication of return shape, synchronous vs long-running behavior, failure modes, or how mode='auto' resolves. The agent is left to discover critical runtime behavior on its own.

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. The description reinforces agent_name (alias list) and mode ('determinista soberano o LLM') but adds no syntax or format detail beyond what the schema already documents for task, context, and mode.

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 ('Ejecuta') and resource ('agente jurídico especializado'), with concrete agent aliases that map to the agent_name parameter. It reads clearly against siblings like agent_list or consulta_maestra, though it never explicitly names an alternative to distinguish itself from them.

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?

Implies usage for 'un objetivo legal complejo' and hints at the deterministic-vs-LLM choice, but gives no explicit when-to-use/when-not guidance or comparison to orchestrator siblings such as caso_ejecutar, consulta_maestra, or caso_analizar. The agent must infer the routing decision.

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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