add_test_cases

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

Discloses the replace behavior and the requirement for targetAnswer for scoring. However, no annotations exist, and the description does not cover side effects like validation, error handling, or what happens if the workspace does not exist.

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?

Five sentences, no redundant information, front-loaded with purpose. Each sentence provides unique value without verbosity.

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?

Covers the replace parameter and test case requirements adequately, but fails to explain workspaceId or return behavior. Given no output schema and 3 parameters, the description is moderately complete.

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?

Adds significant meaning beyond the input schema: explains replace behavior ('clears existing suite') and the condition for targetAnswer (required for scoring, optional for exploratory). WorkspaceId remains undocumented in both schema and description, slightly reducing coverage.

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?

Description clearly states the tool adds test cases to a workspace, with specific verb and resource. However, it does not explicitly differentiate from sibling tools like run_regression_testsuite or loop_regression, which is a minor gap.

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?

Provides clear guidance on when to use 'replace: true' vs 'false' and when to omit targetAnswer. Lacks explicit comparison to alternatives, but the parameter-level advice is helpful.

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