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iampopovich

Allure TestOps MCP

by iampopovich

set_test_case_custom_fields

Add custom field values to a test case through bulk API. Supports grouped and flat value structures for flexible updates.

Instructions

Add custom field values for a test case via bulk API. Supports grouped values [{ customField: { id }, values: [{ id|name }] }] and flat values [{ id|name, customField: { id } }].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
testCaseIdYesTest case ID. Must be a number (integer), not a string.
projectIdNoProject ID. Must be a number (integer), not a string.
projectNameNoProject name (alternative to projectId).
payloadYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It states 'Add custom field values' implying a write operation, but does not clarify whether it overwrites or appends to existing values, idempotency, required permissions, or any side effects. This is insufficient for safe 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 two sentences, front-loading the action and then specifying the payload format. Every word contributes value, and it avoids redundancy with the schema. Highly efficient.

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

Completeness2/5

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

Given no output schema and no annotations, the description lacks information about return values, error handling, whether the tool replaces or merges custom fields, and the role of optional projectId/projectName. For a mutation tool with 4 parameters, this is incomplete.

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?

The input schema covers 75% of parameters with descriptions (testCaseId, projectId, projectName). The tool description adds meaning by explaining the payload structure (grouped vs flat values), which is not detailed in the schema. This helps the agent construct correct payloads.

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 the verb 'Add' and the resource 'custom field values for a test case', mentioning bulk API. It distinguishes from sibling tools like `set_test_case_tags` and `set_test_case_issues` by specifying custom fields, but does not explicitly contrast with them.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like `set_test_case_tags` or `set_test_case_issues`. It does not mention prerequisites, limitations, or exclusions, leaving the agent without context for choosing this tool.

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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