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Export invoices CSV

export_invoices_csv
Read-only

Exports the matching invoices and estimates as CSV text for an accountant: number, type, status, dates, client, currency, subtotal, discount, tax, total, paid and balance. Same filters as the list. Cells that start with = + - or @ are escaped so a spreadsheet does not run them. A Pro feature; large exports are cut at 400,000 characters.

Input Schema

NameRequiredDescriptionDefault
qNoText in the number or the client's name.
toNoIssued up to this day, YYYY-MM-DD.
fromNoIssued from this day on, YYYY-MM-DD.
kindNo
statusNooverdue: sent and past its due date. open: sent and not paid.
boardIdNoOnly the documents of this project (one the user owns).
clientIdNoOnly this client's documents.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnly/destructive annotations, the description discloses three non-obvious behavioral traits: spreadsheet-injection escaping for cells starting with = + - @, the Pro entitlement requirement, and a 400,000-character truncation limit on large exports. These are exactly the operational facts an agent could not infer from annotations or schema.

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?

Four compact sentences, front-loaded with the core action and output columns, followed by filter parity, escaping, and the entitlement/size constraints. No sentence is redundant with structured fields.

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

Completeness5/5

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

There is no output schema, and the description compensates by naming the returned columns and the output medium (CSV text). Combined with the escaping and truncation notes, an agent has everything needed to call and interpret the result.

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 coverage is 86%, so the schema already documents nearly all seven filters including the enum meanings. The description contributes only 'Same filters as the list', which usefully signals parity with list_invoices but adds no per-parameter meaning. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Exports the matching invoices and estimates as CSV text') and even enumerates the exact column set, so an agent knows precisely what it produces. It does not, however, name or contrast itself against the nearest siblings such as export_data or list_invoices, leaving differentiation to inference.

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

Usage Guidelines3/5

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

'for an accountant' and 'Same filters as the list' imply the context and that it is the tabular counterpart to list_invoices, but there is no explicit when-to-use or when-not statement, and no routing away from export_data or export_time_report. Usage is implied rather than stated.

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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