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Export Respondents (SPSS)

export_respondents_spss
Read-only

Exports the respondents pipeline report — one row per respondent across all respondent lists assigned to the survey's publication — as SPSS (.sav), and returns a download link. The link is an unguessable URL with a 128-bit random token; it expires after ~15 minutes. Re-run for a fresh link; never returns inline file bytes. The file contains the contact data of the user's own contact lists for this survey: names, email addresses, custom fields and each contact's personal survey link. The link is temporary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesSurvey publication code — the 8-character code from the survey's public link (e.g. 1a2b3c4d). Returned by list_surveys.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
formatNo
summaryNo
fileNameNo
expiresAtNo
sizeBytesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already mark readOnly/idempotent:false, but the description goes well beyond them: it discloses the ~15-minute link expiry, the unguessable 128-bit token, that a fresh link is produced per run (explaining the non-idempotent hint), that bytes are never returned inline, and that the file contains PII (names, emails, custom fields, personal survey links). This is unusually rich behavioral context.

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?

Front-loaded with the action and scope, then link behavior, then file contents. Efficient overall, though 'The link is temporary' at the end repeats the earlier 'expires after ~15 minutes' and could be cut.

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?

With an output schema present, return format needn't be explained, and the description still covers file contents, link lifecycle, and non-inline delivery. For a single-parameter export tool this is complete enough for correct invocation; only an explicit sibling comparison is missing.

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% and there is a single required 'code' parameter already documented (including an example and its source, list_surveys). The description adds no parameter-level meaning, so the high-coverage baseline of 3 applies.

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?

States a specific verb (Exports), resource (respondents pipeline report), format (.sav SPSS), and scope (one row per respondent across all respondent lists assigned to the survey's publication). The explicit format naming distinguishes it from the export_respondents_csv and export_respondents_xlsx siblings without needing to name them.

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?

Usage is implied by format ('as SPSS (.sav)') and by the re-run guidance ('Re-run for a fresh link'), but the description never explicitly tells the agent when to choose this over export_respondents_csv/xlsx or what distinguishes respondents-pipeline exports from response exports. Adequate but leaves the selection logic to inference.

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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