printing-labs

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

Name	Required	Description
`name`	Yes	Customer's full name
`email`	No	Email address (optional but useful for the team)
`notes`	No	What they want to discuss
`mobile`	Yes	Phone number to call back, with country code
`company`	No	Company name
`preferredTime`	No	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.

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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TDQS

A4/5.0

Disambiguation5/5

Each tool targets a distinct action or resource: product discovery vs pricing vs orders vs meetings vs support. While get-company-info, get-site-info, and get-guide all provide reference material, their scopes are clearly separated (verified facts vs FAQ/how-it-works vs published articles). No two tools appear to do the same thing.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case: book-, cancel-, reschedule-, get-, search-, list-, request-, track-, reorder-, create-. Even exceptions like my-orders and my-invoices fit a possessive pattern that is predictable. No mixed conventions or vague verbs.

Tool Count4/5

24 tools is on the high end but appropriate for the breadth of this server's scope: product catalog, pricing, meetings, orders, invoices, support, guides, company info, and SEO. Each tool fills a specific niche, and none feel redundant. It is slightly heavy but not overwhelming for the domain.

Completeness4/5

The tool surface covers the core workflows well: product search/details/pricing, meeting booking/cancel/reschedule, order viewing/tracking/reordering, quotes, complaints, callbacks, invoices, guides, and company information. A minor gap is the absence of a direct 'place new order' tool, but request-quote and reorder handle the necessary paths, and other interactions (e.g., complains) have clear entry points.

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