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Lucius

by ivanostanin
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Python
Remote

Get Test Case Custom Fields

get_test_case_custom_fields
Read-onlyIdempotent

Get custom field values for a test case by its ID, enabling you to view all recorded attributes in one place.

Instructions

Retrieve custom field values for a specific test case.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoOptional override for the default Project ID.
test_case_idYesThe ID of the test case to retrieve custom fields for
output_formatNoOutput format: 'json' (default) or 'plain'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
test_case_idNo
custom_fieldsNoCustom-field values as named entries or a value map.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv0.14.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "custom_fields": {
+      "anyOf": [
+        {
+          "items": {
+            "additionalProperties": false,
+            "description": "A named custom-field value exposed by test-case details.",
+            "properties": {
+              "name": {
+                "description": "Custom field name.",
+                "title": "Name",
+                "type": "string"
+              },
+              "value": {
+                "description": "Rendered custom field value.",
+                "title": "Value",
+                "type": "string"
+              }
+            },
+            "required": [
+              "name",
+              "value"
+            ],
+            "title": "CustomFieldEntry",
+            "type": "object"
+          },
+          "type": "array"
+        },
+        {
+          "additionalProperties": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "integer"
+              },
+              {
+                "type": "number"
+              },
+              {
+                "type": "boolean"
+              },
+              {
+                "items": {
+                  "type": "string"
+                },
+                "type": "array"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "type": "object"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "default": null,
+      "description": "Custom-field values as named entries or a value map.",
+      "title": "Custom Fields"
+    },
+    "test_case_id": {
+      "anyOf": [
+        {
+          "type": "integer"
+        },
+        {
+          "type": "null"
+        }
+      ],
+      "default": null,
+      "title": "Test Case Id"
+    }
+  },
+  "title": "GetTestCaseCustomFieldsOutput",
+  "type": "object"
+}
  2. First observedv0.11.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds minimal behavioral detail beyond what annotations imply (retrieve operation). No contradiction, but no extra context about error behavior or side effects.

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?

The description is a single concise sentence (8 words). It is front-loaded but could include a brief note about optional parameters or output format. However, it is not wasteful and fits a simple read tool.

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?

Given the presence of output schema, full schema coverage, and annotations, the description is minimally adequate. However, it lacks context about when to use this tool vs. similar custom field tools, which would improve completeness for an AI agent.

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 coverage is 100% with descriptions for all parameters. The description does not add any additional meaning beyond what the schema already provides. Baseline 3 is appropriate since the schema handles parameter documentation.

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 clearly states the action (retrieve), the resource (custom field values), and the scope (for a specific test case). This differentiates it from sibling tools like get_custom_fields (which retrieves definitions) or list_custom_field_values (which may list all values).

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. There are many sibling tools related to custom fields (e.g., list_custom_field_values, create_custom_field_value), but no explicit context or exclusions are given.

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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