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request-callback

Ask the Printing Labs sales team to call the customer back. Creates a real callback request that reaches the team immediately (CRM + email + WhatsApp). Use when someone wants to speak to a human, or when a voice call needs a follow-up. Only submit with the customer's explicit consent and their real number.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCustomer's full name
emailNoEmail address (optional but useful for the team)
notesNoWhat they want to discuss
mobileYesPhone number to call back, with country code
companyNoCompany name
preferredTimeNoWhen to call, as an ACTUAL date and time — 'today 4:30 PM', 'Tue 11 Aug, 10 AM'. If the customer said something relative ('in 1.5 hours', 'do ghante baad'), work it out against the current time first and pass the result: a note reading 'in 1.5 hours' is meaningless to whoever opens it later.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / preferredTime / description
      Previous value: -"When to call, in the customer's words — e.g. 'tomorrow morning', 'after 4pm'"New value: +"When to call, as an ACTUAL date and time — 'today 4:30 PM', 'Tue 11 Aug, 10 AM'. If the customer said something relative ('in 1.5 hours', 'do ghante baad'), work it out against the current time first and pass the result: a note reading 'in 1.5 hours' is meaningless to whoever opens it later."
  2. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It reveals that the request is 'real' and 'reaches the team immediately (CRM + email + WhatsApp)', which indicates immediate side effects. It also discloses the consent requirement, adding important behavioral context. It does not mention potential irreversibility, but the immediate notification is sufficiently transparent.

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 three sentences long, front-loaded with the primary purpose, and every sentence provides necessary information: what it does, when to use it, and a critical constraint. No fluff or redundancy.

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?

The tool has 6 parameters and no output schema, so the description should clarify expectations. It explains the action and immediate effect, and includes key usage criteria. It does not explicitly state what the caller will receive as a response, but for a simple request-creation tool, the description is sufficiently complete.

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

Parameters4/5

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 tool description adds value beyond the schema by emphasizing that the mobile number must be real and requires explicit consent, which relates directly to the 'mobile' parameter. It also reinforces the importance of 'preferredTime' being an actual date, though that is already detailed in the schema.

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's function: 'Ask the Printing Labs sales team to call the customer back' and 'Creates a real callback request.' It uses a specific verb ('ask'/'creates') and resource (callback request), and distinguishes it from sibling tools like book-meeting or raise-complaint.

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 provides clear use cases: 'Use when someone wants to speak to a human, or when a voice call needs a follow-up.' It also includes an important exclusion: 'Only submit with the customer's explicit consent and their real number.' While it does not explicitly name alternative tools, the context is clear enough.

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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