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vokse

Export report

export_report
Read-only

Enqueue an async downloadable export (csv, pdf or xlsx) of a vokse report and return the exportId — the host polls GET /reports/exports/:id for the download URL. For inline data use generate_report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesWhich report to export.
dateToYesLast day, YYYY-MM-DD (inclusive).
formatYesFile format.
dateFromYesFirst day, YYYY-MM-DD.
accountIdsNoOnly these accounts (ids from list_accounts); omit for every account.
householdIdNoHousehold ULID to act on. Call list_households for the covered households; may be omitted only when the connection covers exactly one.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedInput schema / properties / dateFrom / description
      Added value: +"First day, YYYY-MM-DD."
    • addedInput schema / properties / dateTo / description
      Added value: +"Last day, YYYY-MM-DD (inclusive)."
    • addedInput schema / properties / format / description
      Added value: +"File format."
    • addedInput schema / properties / kind / description
      Added value: +"Which report to export."
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

The description discloses the asynchronous behavior and the polling endpoint, which go beyond the readOnlyHint/destructiveHint annotations. It does not mention export expiration or limits, but the annotations already cover the safety profile, and no contradiction with them is evident.

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 sentences, front-loads the core behavior and output, and wastes no words. The alternative tool reference is placed at the end without diluting the main message.

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?

Despite having no output schema, the description tells the agent exactly what to expect (exportId), what to do next (poll GET /reports/exports/:id), and when to choose a sibling tool. Combined with the fully described parameters and annotations, this is complete enough for correct invocation.

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 100%, so the input schema already documents all six parameters in detail. The description adds minimal extra parameter meaning beyond naming the file formats, which are already enumerated in the schema.

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 names a specific action ('Enqueue an async downloadable export'), a clear resource (a vokse report), the supported formats (csv, pdf, xlsx), and the key output (exportId). It also differentiates the tool from the sibling generate_report by pointing out the inline-data alternative.

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

Usage Guidelines5/5

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

It explicitly explains when to use this tool: when an async downloadable export file is needed, and explicitly directs the caller to generate_report for inline data. It also describes the follow-up polling flow, so the agent knows the operational context.

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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