optimize_supports

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

With no annotations, the description fully carries the burden. It discloses that the tool is read-only ('the build is restored'), explains the greedy algorithm, candidate pool selection by measurement not tags, and that it is not a global optimum. This provides complete transparency about behavior.

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 moderately concise, front-loading the purpose and then detailing algorithm and parameters. Each sentence adds value, though some technical jargon could be streamlined. It is well-structured with logical flow.

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 presence of an output schema, the description does not need to explain return values. It covers purpose, behavior, parameter usage, and next steps. It explains read-only nature and algorithm details, making it complete for a tool of this complexity.

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 schema has 0% description coverage, so the description must compensate. It explains the interaction between goals and metric, gives an example of goals format, and describes the candidates parameter. However, max_supports (default 5) is not explicitly linked to 'sockets full' and metric's default is noted but not elaborated.

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 'Choose the best support-gem set for the active main skill (engine-measured).' It uses a specific verb and resource, distinguishes from sibling tools like find_supports_for (which lists supports) and set_skill (which applies), and adds scope (active main skill).

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 context for when to use the tool by stating 'Supports are usually a build's biggest more multiplier' and instructs 'Apply the result with set_skill.' It explains parameter choices (e.g., goals for multi-objective, candidates for wider search) but does not explicitly contrast with alternatives like optimize_item or find_supports_for.

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