generate_mock_variants

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

No annotations are provided, so the description must carry the transparency burden. It mentions that outputs are structurally valid but value-diverse and that a seed allows reproducibility. However, it does not disclose safety aspects (e.g., no destructive side effects) or any rate limits or authentication needs. Since generation tools are generally safe, this is adequate but not fully transparent.

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 extremely concise: two sentences that front-load the purpose and usage, with no extraneous content. Every sentence serves a clear function.

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 simplicity (3 parameters, no output schema), the description covers the key use cases and differentiates from siblings. It mentions seed for CI and the number of variants. It could explicitly state the output format (array of objects matching schema), but that is implicit for a mock generation tool.

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 coverage is 100%, with all three parameters having descriptions in the schema. The description adds value by emphasizing the seed's role in CI reproducibility, but otherwise it does not significantly expand on schema descriptions. Baseline 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 generates N structurally valid but value-diverse mocks from a Zod schema for property-based testing. It distinguishes from sibling generate_valid_mock by specifying when to use this tool (when deterministic output is insufficient).

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 explicitly says to use this tool when generate_valid_mock is too deterministic and you need varied inputs to surface edge cases. It also advises supplying a seed for reproducible output in CI. However, it does not explicitly state when not to use it (e.g., when a single valid mock is needed), but the contrast with generate_valid_mock implies the alternative.

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