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update_signup_field_values

Update existing signup-field answers in bulk. Use signup-field value IDs (from list_signup_field_values) to update records across learners; create signup-field values for answers that don't exist yet.

Instructions

Change existing signup-field answers. This is a BATCH operation.

    Each item is `{id, value}` where `id` is the signup-field-VALUE id - the `id`
    returned by `list_signup_field_values`. This is NOT the signup-FIELD id that
    `create_signup_field_values` takes. The two calls key the same conceptual row by
    different identifiers, so an id that works in one will not work in the other.

    Items may span different learners; the value id already says whose answer it is.

    To set an answer that does not exist yet, use `create_signup_field_values`,
    which upserts.

    Requires the `signup-fields:write` OAuth scope.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valuesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYes
noteYes
totalYes
failedYes
succeededYes
Install Server

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations, the description discloses batch behavior, the non-obvious distinction between signup-field-value ids and signup-field ids, the fact that items may involve different learners, and the required OAuth scope. These are valuable behavioral details that materially reduce the risk of incorrect invocation.

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 longer than average but every sentence adds necessary context: batch nature, id semantics, cross-learner behavior, the alternative upsert tool, and required auth. It is front-loaded with the core purpose and uses code formatting to make the item shape and warning clear.

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?

For a single-parameter batch update tool, the description covers the operation scope, item schema, id provenance, exclusions for non-existing answers, and authentication. Combined with the output schema and annotations, nothing essential is missing for an agent to call it correctly.

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

Parameters5/5

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

Schema coverage is 0%, so the description carries the full burden for parameter meaning. It fully explains the single `values` parameter: each item is `{id, value}`, the `id` is specifically the signup-field-VALUE id returned by `list_signup_field_values`, and it warns against confusing it with the signup-field id. This compensates completely for the bare 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 opens with a specific verb and resource: 'Change existing signup-field answers.' It immediately identifies this as a batch operation and explicitly contrasts its id semantics with the sibling `create_signup_field_values`, so an agent can distinguish it without opening schemas.

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?

The description gives explicit when-to-use guidance: use this for existing answers, and use `create_signup_field_values` when the answer does not exist yet because that call upserts. It also clarifies that items may span learners, removing a potential hesitation about cross-learner batches.

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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