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Start Companies LLC Formation

Submit an LLC formation request

create_llc_lead

Registers the LLC formation request, emails the user a confirmation with their reference number, and returns the payment link. The user does not need to fill in any web form afterwards: everything was captured here. If they are not ready to pay, hand them off to a person, not to a form. Call this ONLY after the user has explicitly confirmed the package. Start Companies replies by email within 24 hours.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paisYesCountry of residence of the owner.
emailYesContact email.
estadoNoUS state where the LLC will be formed.
nombreYesFull name of the owner.
sociosYesTotal number of members, including the owner.
paqueteYesThe package the user confirmed.
whatsappYesWhatsApp number including country code. E.g. +54 9 11 5555 5555.
actividadYesWhat the business does. E.g. "marketing agency".
nombre_empresaNoDesired LLC name, without the "LLC" suffix.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations are minimal (readOnlyHint false, etc.), so description carries the burden. It discloses that the tool registers the request, sends an email with reference, returns a payment link, and that Start Companies replies within 24 hours. It does not discuss idempotency or error states, but covers core behavior well.

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

Conciseness5/5

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

Four sentences with no fluff. The first sentence encapsulates the main purpose and outputs. Subsequent sentences add precise usage constraints and post-call expectations. Every sentence earns its place.

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?

Given 9 parameters (7 required) and no output schema, the description covers the key actions, preconditions, and a downstream expectation. It lacks details on return value format or error cases, but for a form submission tool it is substantially complete.

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 coverage is 100% with individual parameter descriptions, so baseline is 3. The description adds meta-context that 'everything was captured here' (reassuring completeness) and links 'paquete' to package confirmation, but does not explain individual parameters beyond schema. Adequate.

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?

The description clearly states the tool registers an LLC formation request, sends a confirmation email, and returns a payment link. It distinguishes from sibling tools (all read/info tools except start_itin_application) as the creation action, and specifies the prerequisite of explicit package confirmation, differentiating from recommend_llc_package.

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

Usage Guidelines5/5

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

Explicitly states 'Call this ONLY after the user has explicitly confirmed the package.' Also advises handing off to a person if not ready to pay, providing clear when-to-use and when-not-to-use guidance. Though it doesn't name sibling alternatives, the precondition is unambiguous.

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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