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NeuroBlockFoundation

ExtractorLead MCP Server

Lanzar relleno de lista

start_list_enrichment

Starts filling missing emails and phone numbers in an uploaded lead list within an approved credit cap, returning a job to monitor.

Instructions

Lanza el relleno de huecos de una lista. Consume créditos hasta credit_cap.

credit_cap: tope de gasto que el usuario ha aprobado (usa el tope_sugerido de preview_list_enrichment si no dice otro). Sigue el trabajo con get_list_enrichment.

Input Schema

NameRequiredDescriptionDefault
leadsNo
file_pathNo
credit_capYes
wants_phoneNo
phone_for_allNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

The annotations already declare readOnly=false, idempotent=false and openWorld=true; the description adds the genuinely non-obvious fact that the call burns credits up to credit_cap, which is valuable context. However, it does not warn that repeated launches create new jobs (non-idempotent) or that credit spend is irreversible once under way, which is the main behavioral risk of this tool.

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?

Two short paragraphs, front-loaded with the action and the cost implication, with the parameter note in its own block. Every sentence carries information; no filler or repetition of the title.

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?

An output schema exists, so return values need not be explained, but for a non-idempotent job-launcher that spends the user's credits, the definition omits how the list is supplied (leads array vs file_path) and what the phone-related flags do. That is a substantial gap given 0% schema description coverage.

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

Parameters2/5

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

Schema description coverage is 0% across 5 parameters, and the description only explains credit_cap (with useful guidance on where the value comes from). The four remaining inputs — leads, file_path, wants_phone, phone_for_all — are completely undocumented, and the mutually exclusive nature of leads vs file_path is left entirely to inference.

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 and resource: launching the gap-filling ('relleno de huecos') of a list, and names the concrete objects it interacts with (credit_cap, preview_list_enrichment, get_list_enrichment). It is clearly distinguishable from its siblings, though the phrase 'relleno de huecos de una lista' is somewhat idiomatic and leaves the nature of the enrichment implicit.

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 explicit operational routing: read the suggested cap from preview_list_enrichment when the user has not specified one, and poll progress with get_list_enrichment. It stops short of stating when NOT to use it (e.g. bulk vs list enrichment, or re-launching an already-running job).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.