generate_tests

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 states the tool 'generates test case suggestions,' which implies a read-only or creative operation, but it doesn't disclose any behavioral traits such as whether it modifies data, requires specific inputs beyond the schema, has rate limits, or what the output format might be. This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence: 'Generates test case suggestions for a feature or function.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity, earning a high score for conciseness.

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 states the purpose but lacks behavioral details, usage guidelines, and output information. With no output schema, the description doesn't explain return values, which is a gap, but it's not severe enough to score lower than 3, as it meets the minimum viable threshold.

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 ('feature' and 'type' with enum values). The description adds no additional meaning beyond what the schema provides, such as examples or constraints. According to the rules, with high schema coverage (>80%), the baseline is 3, which is appropriate here as the schema does the heavy lifting.

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: 'Generates test case suggestions for a feature or function.' It specifies the verb ('generates') and resource ('test case suggestions'), making it easy to understand what the tool does. However, it doesn't differentiate from sibling tools like 'validate_code' or 'lint_code', which might also relate to testing or code quality, so it doesn't reach the highest score.

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 doesn't mention any context, prerequisites, or exclusions, and with sibling tools like 'validate_code' or 'debug_problem' that might overlap in testing scenarios, the lack of differentiation leaves the agent without clear usage instructions.

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