Get company info
paymo_get_companyFetch the company (account) info and settings: name, default currency, timezone, working days, invoice numbering. Paymo: GET /api/company.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
paymo_get_companyFetch the company (account) info and settings: name, default currency, timezone, working days, invoice numbering. Paymo: GET /api/company.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the read-only safety profile is covered by structured data. The description adds useful context by naming the specific settings fields returned, but says nothing about authentication, scoping (single company per account?), or freshness. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences, field list front-loaded after the core purpose. The trailing API endpoint reference ('Paymo: GET /api/company') is informational filler for an agent but costs little.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
A zero-parameter read tool with no output schema, so the description carrying the return-field list is exactly the needed compensation. Nothing critical for correct invocation is absent; only sibling differentiation and usage context are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline is 4. No misleading parameter hints are present.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Fetch') and resource ('company/account info and settings') and enumerates the concrete fields returned (name, default currency, timezone, working days, invoice numbering). It is not tautological like the title. It stops short of distinguishing itself from the similar-sounding sibling paymo_get_me, which also retrieves account/user-level data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No indication of when to call this tool versus alternatives such as paymo_get_me, nor any prerequisites or context for its use. The use case is only weakly implied by the field list. An agent must guess when account-level settings are the right source.
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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