suggest_fix

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds genuine behavioral context by stating what the tool returns: a detected smell plus a step-by-step fix recipe and refactoring prompt — valuable because no output schema exists.

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?

Two tight sentences with zero filler; the core purpose is front-loaded and the output description follows immediately.

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 simple read-only, three-parameter tool with no output schema, the description covers what the tool does and roughly what comes back. The only notable omission is the role of the locale parameter and the detection-vs-lookup behavior of smell_id.

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 67%, with 'issue' and 'smell_id' documented in the schema and only 'locale' undocumented. The description adds no parameter-level meaning (e.g., whether omitting smell_id triggers detection, or what locale localizes), so it does not compensate for the gap beyond the baseline.

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 names a specific verb+resource ('Get a fix suggestion for a UX issue') and clarifies the payoff (step-by-step recipe plus refactoring prompt). It is reasonably distinct from siblings like list_smells or get_smell, though it never explicitly contrasts itself with detect_smell, which it partly duplicates by also detecting the smell.

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: call this when you have a UX issue and want remediation rather than mere detection. There is no explicit when-not guidance, no mention of when to prefer detect_smell or get_smell first, and no stated prerequisite for supplying an existing smell_id.

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