get_test_run_result_statuses

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a read operation ('Get list'), which implies it's non-destructive, but doesn't mention any behavioral traits such as authentication requirements, rate limits, error handling, or response format details. For a tool with no annotations, this is a significant gap in transparency.

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?

The description is concise and well-structured, consisting of two sentences that directly state the tool's purpose and usage context without unnecessary details. It's front-loaded with the core action and resource, making it easy to understand quickly. Every sentence earns its place by adding value.

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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and context but lacks details on behavioral aspects, output expectations, and usage guidelines. Without annotations or an output schema, the description should do more to compensate, but it falls short of being fully complete for effective tool selection and invocation.

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 has 100% description coverage, with clear documentation for both parameters ('project' and 'format'). The description doesn't add any parameter-specific semantics beyond what the schema provides, such as explaining the difference between 'raw' and 'formatted' outputs or detailing project key formats. Given the high schema coverage, a baseline score of 3 is appropriate.

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?

The description clearly states the tool's purpose: 'Get list of Result Statuses configured for a project.' It specifies the resource (Result Statuses) and the action (Get list), and mentions their usage context ('used when assigning results to Test Cases'). However, it doesn't explicitly differentiate from sibling tools that might also retrieve project-related data, such as 'get_project_milestones' or 'get_automation_states', which slightly reduces clarity.

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?

The description provides no guidance on when to use this tool versus alternatives. It mentions that the statuses are 'used when assigning results to Test Cases,' which implies a context but doesn't specify prerequisites, exclusions, or direct comparisons to sibling tools like 'get_automation_states' or 'get_test_run_by_id.' This lack of explicit usage instructions limits its effectiveness for an AI agent.

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