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List expenses

paymo_list_expenses
Read-only

List expenses (id, client_id, project_id, user_id, amount, currency, date, notes, invoiced, tags). Paymo: GET /api/expenses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax items to return (default 100, max 500). Paymo has no pagination; results beyond this are truncated.
whereNoExtra raw Paymo filter ANDed onto the typed ones, e.g. `billable=true` or `name like Website`. Operators: = > >= < <= != like, not like, in (a,b), not in (a,b).
date_toNoOnly expenses dated on/before this day.
invoicedNotrue = already invoiced, false = not yet invoiced.
client_idNoOnly expenses for this client.
date_fromNoOnly expenses dated on/after this day.
project_idNoOnly expenses for this project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

B3.2/5.0
Behavior3/5

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

annotations already declare readOnlyHint=true, so the safety profile is covered by structured data. The description's only added behavioral content is the shape of returned records (id, client_id, project_id, user_id, amount, currency, date, notes, invoiced, tags), which is genuinely useful given there is no output schema, plus the underlying endpoint. It says nothing about truncation, ordering, or default result volume.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight clauses with the core verb-resource claim front-loaded and no filler. The trailing 'Paymo: GET /api/expenses.' is marginally redundant with the tool name but cheap and adds endpoint provenance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the returned-field enumeration is a real contribution toward completeness, and no parameters are required. However, the description omits the truncation/no-pagination caveat that the schema surfaces only on the limit parameter, and gives no indication of result ordering or typical volume for a list endpoint.

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 100%, so every parameter (limit, where, date_from, date_to, invoiced, client_id, project_id) is already documented with semantics, operators, and defaults in the schema itself. The description adds no parameter-level information at all, so the baseline 3 applies.

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?

States a specific verb and resource ('List expenses') and enumerates the fields the records contain, so the agent knows exactly what object is being fetched. It is unambiguous against siblings like paymo_list_invoices or paymo_list_time_entries, though it never explicitly contrasts itself with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives. The parenthetical field list reads like a description of returned columns rather than filters, which could momentarily mislead an agent about what this tool accepts, since the actual filter parameters are client_id, project_id, date range, invoiced and where.

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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