Skip to main content
Glama

kiwi_update_test_cases

Batch update multiple test cases with the same field values, reporting per-case success or failure.

Instructions

Apply the same values patch to many cases (mirrors TestRail update_cases). Runs one TestCase.update per id and reports per-id success/failure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valuesYes
case_idsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explicitly reveals that the operation is non-atomic (one TestCase.update per id) and that results report per-id success/failure, which is meaningful behavioral information beyond the tool name alone. It does not detail output format or failure continuation, but the key non-obvious behavior is covered.

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 front-loaded: the core operation appears first, followed by the TestRail reference and the per-id execution detail. Every sentence contributes useful information without repeating schema or annotation content.

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

Completeness3/5

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

The description adequately explains what the tool does and its batch behavior, but for a tool with no annotations, no output schema, and an open `values` object, it lacks the exact return shape, valid value keys, and what happens when individual updates fail. This is sufficient to select the tool but not fully sufficient to invoke it with complete confidence.

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 0%, so the description must compensate. It does add meaning by describing `values` as a shared patch applied to many `case_ids`, which is helpful. However, `values` is an unconstrained object with additionalProperties true, and the description does not enumerate or link to the valid fields, leaving a significant semantic gap.

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?

Description states a specific action ('Apply the same values patch to many cases') and resource (test cases), and clearly distinguishes itself from kiwi_update_test_case by emphasizing bulk operation over many ids. The detail 'Runs one TestCase.update per id' further clarifies the exact operation.

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?

The description clearly conveys the intended usage: updating multiple cases with an identical `values` patch. It does not explicitly name alternatives or state exclusions such as 'use kiwi_update_test_case for a single case', but the bulk-vs-singular context is strong enough to guide tool selection.

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