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Glama

Set Validation Status on Submissions

kobo_validate_submissions
Idempotent

Clean survey responses by marking Kobo submissions as approved, not approved, or on hold while retaining rows for review.

Instructions

Mark submissions as approved, not approved, or on hold — Kobo's data-cleaning workflow.

This is the non-destructive way to handle suspect responses: the row stays in the database and in exports, carrying its status, instead of being deleted.

Args:

  • uid (string): asset uid of the form

  • submission_ids (array of strings): the "_id" values to mark

  • status: 'validation_status_approved' | 'validation_status_not_approved' | 'validation_status_on_hold'

Returns: how many submissions were updated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uidYesAsset uid of the form
statusYesValidation status to apply, as shown in Kobo's data table
submission_idsYesIds of the submissions to mark

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already indicate destructiveHint=false and idempotentHint=true, and the description adds valuable non-destructive behavioral detail: the row remains in the database and exports with its status rather than being removed. It also discloses the return value (count of updated submissions), which the annotations do not provide.

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 compact and well-structured: a one-line purpose, a one-sentence behavioral clarification, a concise Args list, and a Returns note. No filler or redundant restatement of the tool name or title.

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 straightforward 3-parameter mutation tool with no output schema, the description is complete: it explains what the tool does, why it exists, how to supply parameters, and what the caller receives in return. The annotations cover idempotency and non-destructiveness, so no critical operational context is missing.

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. The description adds useful clarification beyond the schema by specifying submission_ids are the '_id' values to mark and enumerating the exact allowed status strings. This helps the agent construct the correct request without needing to infer semantics from the generic schema descriptions.

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: 'Mark submissions as approved, not approved, or on hold.' It clearly identifies the operation (setting validation status) and distinguishes it from sibling tools like kobo_delete_submissions by noting this is non-destructive and preserves the row in the database and exports.

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 explicitly frames the tool as the non-destructive way to handle suspect responses and contrasts it with deletion: 'the row stays in the database and in exports, carrying its status, instead of being deleted.' This gives the agent a clear when-to-use and when-not-to-use signal relative to destructive alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.