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Update Survey Response

update_survey_response
DestructiveIdempotent

Updates an existing response addressed by PersonalizedID; the response must exist, otherwise 'Result case not found.'. MERGE semantics: only the questions addressed in Items are changed, unmentioned answers stay as they are. IsCompleted is applied only when explicitly sent and never reverts a completed response; the completion date is set by the server. Verified by readback: the response is re-read from the survey's stored data afterwards and the reply reports the values that are actually stored for the variables you sent. That read costs one heavy-class request. Note: updating a response may fire the survey's configured ResponseRecieved webhooks, which send outbound HTTPS to the subscriber's external endpoint.

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.
resultCaseYesThe update: personalizedID (required — the response to change), items — the answers to merge, and optionally isCompleted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNoWhat the call did, verified, refused or previewed — the complete human-readable outcome.
previewNotrue when the call was a preview (confirm not passed): nothing was changed.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the annotations: discloses merge (only named items change), the non-reverting completion semantics, server-set completion date, a readback verification that costs one heavy-class request, and the side effect of firing ResponseRecieved webhooks over outbound HTTPS. This is unusually rich behavioral disclosure for a mutation tool.

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-loads the core behavior and the merge rule before the cost and webhook caveats. Dense but nearly every clause carries operational weight; it could be trimmed slightly without loss.

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?

Even though an output schema exists, the description covers error behavior, side effects, cost, and update semantics - everything an agent needs to invoke this correctly on a nested-object mutation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% so the baseline is 3, but the description reinforces the semantics of key fields - personalizedID is required on update, items are a merge rather than a replace, and isCompleted is applied only when explicitly sent.

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 (Updates) and resource (an existing response) and its addressing key (PersonalizedID), plus the failure condition. Clearly distinguishable from create_survey_response and get_survey_response.

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

Usage Guidelines4/5

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

Explains the preconditions (response must exist) and the MERGE update model, which tells an agent when this is the right tool versus creating a new response. It stops short of naming sibling tools explicitly, so it is clear context without explicit alternatives.

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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