Promote candidate settings to LM Studio

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

Annotations indicate it is not read-only and not destructive. The description adds that it performs a backup before updating and that 'Handy remains read-only,' providing useful behavioral context beyond what annotations offer.

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 sentences, no waste. The first sentence delivers the core action and conditions; the second adds a relevant constraint. Information is front-loaded and concise.

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 single-parameter tool with no output schema, the description covers prerequisites and side effects. It could be improved by clarifying backup location or return values, but overall it provides adequate context for the tool's use.

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 description coverage is 0%, so the description bears full burden. It does not explicitly describe the candidateId parameter's meaning or format, only indirectly referring to a 'frozen candidate.' This is insufficient for clarity.

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 verb 'backs up and updates' and the resource 'LM Studio's per-model defaults' with specific conditions ('frozen candidate that completed holdout evaluation'). This distinguishes it from siblings like 'freeze_prompt_candidate' and 'plan_lm_studio_promotion'.

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 implies the tool should be used 'after form confirmation' and only for 'frozen candidate that completed holdout evaluation', but does not explicitly name alternative tools or state when not to use it. It provides clear prerequisites but lacks explicit exclusions.

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