list_test_cases

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

No annotations are provided, so the description must fully disclose behavioral traits. It only mentions 'Supports pagination and various filtering options' without specifying behavior like what the response contains, pagination details, error handling, or any side effects. This is insufficient for a complex tool with 11 parameters.

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 with two sentences. The first states the core purpose, and the second adds a usage hint. No extraneous information; every sentence earns its place.

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 complexity (11 parameters, no output schema), the description is minimal. It does not explain the response structure, pagination behavior (e.g., default limit 20), or error conditions. More context would help the agent use the tool effectively.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds no new information beyond what the schema already provides (e.g., 'Supports pagination and various filtering options' is redundant). It does not enhance parameter understanding.

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 'List test cases from a project in QA Sphere', specifying the verb (list), resource (test cases), and context (from a project). This distinguishes it from sibling tools like get_test_case (single item) and list_test_cases_folders (folders), as well as get_project and list_projects.

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 explicit usage guidance: 'Usually it makes sense to call get_project tool first to get the project context.' This tells the agent when to use this tool in a sequence. However, it does not mention when not to use it or alternatives beyond the suggested precondition.

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