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Field Service Business Platform by Doing Work

network_cancelBooking

Cancel a booked customer job (owner or office). The customer's deposit is refunded in full automatically, including Doing Work's fee. Only the deposit is refunded; anything else the customer paid on the invoice is the shop's to refund with invoices.refund. Moves money: a no_money key cannot call it, a worker needs take_money, and an agent cancel above the shop's agent refund cap waits for the owner.

Input Schema

NameRequiredDescriptionDefault
job_idYes
reasonNo
shop_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses that the tool moves money, refunds the deposit in full including Doing Work's fee, and does not refund other invoice payments. It also states concrete authorization behavior: no_money keys cannot call it, workers need take_money, and agent cancels above the shop's refund cap wait for the owner.

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 tight sentences: purpose first, refund scope second, authorization/money movement third. Every sentence adds distinct, useful information without repetition 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?

For a money-moving cancellation tool with no annotations, the description covers the critical behavioral and authorization details thoroughly, and an output schema exists so return values do not need explanation here. The main completeness gap is parameter-level semantics, especially the undocumented reason field.

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

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for three parameters, so the description must compensate for undocumented parameters. It implies shop_id and job_id through the concept of canceling a booked customer job, but it never explains them, and it does not mention the optional reason parameter at all. This leaves meaningful gaps for an agent filling the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: cancel a booked customer job, with the allowed actor scope (owner or office). It also distinguishes the refund scope by pointing to invoices.refund for non-deposit amounts. It does not explicitly differentiate itself from adjacent cancellation tools such as visits_cancel, but the core purpose is clear.

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?

It gives clear usage context: use this for canceling a booked customer job, and use invoices.refund for anything beyond the deposit. It also states permission-based constraints for who can successfully call it. It lacks explicit when-not-to-use guidance against other cancellation siblings, but the alternative for refund scope is clearly named.

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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