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Oleksandr-Kliuiev

poweroffice-mcp

Create a PowerOffice customer

poweroffice_create_customer

Creates a customer record in PowerOffice Go using provided details, writing only after you explicitly confirm the exact data.

Instructions

Create one customer with POST /Customers. This writes to the configured PowerOffice client. Set confirm=true only after the user has explicitly approved the exact customer data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmYesRequired explicit confirmation that this exact customer may be created
customerYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resourceYes
Behavior4/5

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

Annotations already indicate this is a write operation and not idempotent. The description adds valuable behavioral context beyond that: it writes to the configured PowerOffice client and requires explicit user approval before confirm=true. No contradiction with annotations was found.

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 short sentences, front-loads the core action, and each sentence earns its place. The approval warning is critical and placed at the end without unnecessary padding.

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 that a detailed output schema exists and annotations cover the write/non-idempotent behavior, the description is largely sufficient. It captures the essential operational context: endpooint, target client, and the mandatory user-approval condition. It does not explain duplicate risk explicitly, but the non-idempotent annotation covers that.

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%, with confirm documented but customer not described. The description adds useful meaning for confirm ('only after the user has explicitly approved the exact customer data') but does not clarify semantics of the large customer object beyond what the schema's field names and constraints already convey.

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 states a specific action ('Create one customer'), a concrete HTTP resource ('POST /Customers'), and a clear scope ('one customer'). This clearly distinguishes it from siblings like update_customer, search_customers, and get_customer without needing to open the schema.

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 gives clear context for when to use the tool: creating exactly one customer, and it adds a critical usage guardrail around confirm=true. However, it does not explicitly name alternatives such as update_customer for existing customers or search_customers for lookups, so exclusion guidance is absent.

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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