get_result_fields
Retrieve all available result fields in TestRail to identify which fields can be used when submitting test results.
Instructions
List available result fields
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve all available result fields in TestRail to identify which fields can be used when submitting test results.
List available result fields
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
'List' clearly signals a non-mutating enumeration and identifies what is returned. However, with no annotations and no output schema, the description does not clarify whether both system and custom fields are returned, what per-field structure to expect, or whether the set of available fields is project-dependent. It is minimally transparent but not richly so.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One short sentence with no filler; every word ('List', 'available', 'result fields') earns its place, and the main predicate is front-loaded. Additional wording would mostly repeat API/context information rather than improve clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter metadata listing tool, 'List available result fields' is largely sufficient for an agent to select and invoke the call. There is no output schema, so the description necessarily carries the burden of outlining the return concept, and 'result fields' does that. It could be more explicit about result-field structure, but the low complexity keeps the gaps minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema declares zero parameters and schema description coverage is trivially 100%, so there are no parameter semantics to document. The baseline of 4 for a parameterless tool applies; the description does not need to add input-level detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a clear action ('List') and resource ('available result fields'), so an agent can infer that this endpoint returns result-field metadata. It distinguishes from siblings like get_case_fields and get_results through the 'result fields' scope, though it does not explicitly call out that distinction. It is not a pure tautology because it adds the 'List available' scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is only implied: call this when the agent needs available result fields. It does not provide explicit when-to-use vs. when-not-to-use guidance, nor does it mention alternatives such as get_case_fields for case fields. The resource name itself carries most of the routing information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.