generate_test

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

With no annotations, the description carries the full behavioral disclosure burden, but it only mentions framework auto-detection, which is already documented in the schema. It does not disclose output format, side effects, or any operational constraints, leaving a transparency gap for a generation tool.

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 sentence that front-loads the core purpose and includes a useful feature note. Every word contributes, with no filler or redundancy, making it highly efficient.

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?

For a moderate-complexity tool with no output schema or annotations, the description covers purpose and a key feature but omits important context such as the return value of the tool and any behavioral expectations beyond generation. It is minimally viable but has clear gaps.

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?

All four parameters have schema descriptions (100% coverage), so the schema already handles parameter semantics. The description adds no extra meaning beyond referencing framework auto-detection and agent usage, both of which are already in the schema.

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 a specific verb and resource ('Generate tests for code') and distinguishes this tool from sibling code-related tools like debug_with, refactor_with, and explain_with. It also clarifies the agent-driven nature, making its purpose unmistakable.

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?

Usage is implied (if you need tests, use this tool) but not explicitly stated. It does not mention when to prefer it over alternatives like ask_agent or delegate_task, nor any exclusions or preconditions.

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