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request_booking

KROK 3 rezervácie: vytvorí ČAKAJÚCU rezerváciu výmeny batérie u partnera (token z verify_code; customer_email MUSÍ byť overený e-mail). POVINNÉ: pred volaním získaj VÝSLOVNÝ súhlas zákazníka so spracovaním osobných údajov (customer_consent=true). Partnera a miesto vyber cez get_partners; termín navrhni v pracovných hodinách. Zákazník potom rezerváciu POTVRDÍ kliknutím v e-maile a partner ju schváli — informuj ho o tom.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesToken z verify_code
partner_codeYesKód partnera z get_partners
scheduled_atYesTermín ISO 8601, napr. 2026-07-25T10:00:00+02:00
vehicle_makeNo
vehicle_yearNo
customer_nameYes
vehicle_modelNo
customer_emailYesOverený e-mail (rovnaký ako pri verify_code)
customer_phoneYes
customer_consentYesVýslovný súhlas zákazníka (GDPR) — musí byť true

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?

With no annotations, the description carries full burden. It discloses the reservation is pending, requires consent, and involves an email-based confirmation and partner approval. It doesn't mention idempotency or side effects, but for a creation tool, the pending state and required follow-up actions are adequately described.

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?

The description is dense and front-loaded, conveying purpose, prerequisites, and flow in a few sentences without redundancy. Every sentence adds value.

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 the complexity (10 params, no output schema, no annotations), the description covers purpose, prerequisites, partner selection, time suggestion, and the confirmation flow. It misses error handling or return value info, but the main workflow is well-described.

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 50%, and the description adds context for key parameters: token (from verify_code), customer_email (must be verified), customer_consent (must be true), partner_code (from get_partners), scheduled_at (during working hours). However, it does not cover vehicle_make, vehicle_model, vehicle_year, customer_name, customer_phone beyond schema, so it only partially compensates for the missing schema descriptions.

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 explicitly states it creates a PENDING reservation for battery exchange at a partner, which is a specific verb+resource. It distinguishes itself from siblings like verify_code and get_partners by being the step that creates the actual booking after verification and partner selection.

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?

The description clearly states prerequisites: token from verify_code, verified email, explicit consent (customer_consent=true). It advises selecting partner via get_partners and suggesting time during working hours. It also explains the post-call flow (customer confirms via email, partner approves). It lacks explicit when-not-to-use but provides sufficient context.

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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