printing-labs

raise-complaint

File a complaint for a customer who is unhappy with something Printing Labs did — a late or wrong delivery, a quality problem, a billing error, a request nobody answered. Creates a real ticket: the customer is acknowledged by email (and WhatsApp when possible) with a reference, the team that can actually fix it is alerted, and a task with a deadline lands on their board. Use it the moment somebody complains; do NOT use it for a question, a quote chase or a price negotiation.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	No	Who is complaining
`what`	Yes	What went wrong, in the customer's own words. Do not soften it.
`email`	No	Their email address — needed to send the acknowledgement
`phone`	No	Their number with country code
`callId`	No	Only for a voice agent filing this during a live call: the id of that call, so the team can open the recording beside the ticket. Leave it out entirely if you do not have one — NEVER guess or invent it, because a wrong call id sends the handler to the wrong recording.
`company`	No	Their company
`orderRef`	No	Order or invoice number if they quote one
`severity`	No	Only if they make it explicit — 'low', 'medium' or 'high'. Otherwise leave it out and it is judged from what they said.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedAug 13, 2026

addedInput schema / properties / callId

Added value: +{
+  "description": "Only for a voice agent filing this during a live call: the id of that call, so the team can open the recording beside the ticket. Leave it out entirely if you do not have one — NEVER guess or invent it, because a wrong call id sends the handler to the wrong recording.",
+  "type": "string"
+}

AddedAug 10, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations provided, the description takes on the full burden of transparency. It discloses that the tool creates a real ticket, sends an email/WhatsApp acknowledgment with a reference, alerts the fix-it team, and adds a task with a deadline to a board. This goes beyond a minimal description and informs the agent of concrete side effects.

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 two sentences, front-loaded with the core purpose, followed by effects and usage direction. Every sentence adds value, with no redundancy or filler.

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 description covers key context: what triggers use, what happens after filing (acknowledgment, alert, task), and the exclusion cases. Minor gap: it does not explicitly state the tool's return value (e.g., ticket ID), but the mention of 'reference' implies useful output. Overall, it is complete enough given the absence of an output schema.

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?

The input schema already provides 100% coverage with descriptions for all 8 parameters, so the baseline is 3. The description adds general context (e.g., complaint categories) but does not provide additional parameter-level meaning beyond what the schema states.

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 purpose: 'File a complaint for a customer who is unhappy with something Printing Labs did', with concrete examples like late/wrong delivery, quality problems, billing errors, and unanswered requests. It explicitly distinguishes this from non-complaint interactions, making it unique among sibling tools.

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?

Usage guidance is explicit: 'Use it the moment somebody complains' and 'do NOT use it for a question, a quote chase or a price negotiation.' This provides clear when-to-use and when-not-to-use directions, helping the agent choose this tool over alternatives like request-quote.

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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