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Export responses by token

limesurvey_export_responses_by_token
Read-onlyIdempotent

Export responses for specific participant tokens as a base64-encoded document in CSV, HTML, PDF, XLS, or JSON.

Instructions

Export responses for selected participant tokens as a base64-encoded document.

Calls LimeSurvey RemoteControl method export_responses_by_token. Authentication uses the configured service account; do not provide a session key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoOptional response fields to export.
tokensYesOne participant token or a list of tokens to export.
survey_idYesNumeric LimeSurvey survey ID.
heading_typeNoColumn heading style.
document_typeYesExport type such as csv, html, pdf, xls, or json.
language_codeNoLimeSurvey language code; null uses the survey default.
response_typeNoAnswer text format.
response_formatNoOutput format. JSON preserves the complete structured result; Markdown is optimized for reading.json
completion_statusNoCompletion filter.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodYes
resultYes
truncatedNo
truncation_messageNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds value by noting the output is a base64-encoded document and calling a specific API method. This provides behavioral context beyond annotations, though it could mention potential size limits or encoding details.

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 extremely concise: two sentences covering the main action and one sentence about authentication. It front-loads the core purpose and avoids unnecessary details, efficiently using every word.

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

Completeness4/5

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

Given the complexity (9 parameters, 3 required), the presence of an output schema, and strong annotations, the description is fairly complete. It covers the tool's purpose, output format, and authentication. However, it does not explain how to decode or use the base64 result, which is a minor gap for a complete understanding.

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 the input schema already fully documents each parameter. The description adds no additional per-parameter meaning, making it a baseline scenario. It does not compensate beyond the schema's rich enum and description details.

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?

The description clearly states it exports responses for selected tokens as a base64-encoded document. It accurately reflects the action implied by the tool name. However, it does not explicitly differentiate from similar sibling tools like limesurvey_export_responses or limesurvey_export_responses_by_token_to_file, relying on the name for distinction.

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?

The description mentions authentication context (no session key) and the target LimeSurvey method, providing some usage guidance. However, it does not specify when to use this tool versus alternatives (e.g., when you have tokens vs. when you don't), nor provide any exclusions or prerequisites.

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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