set_feature

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

No annotations are provided, so the description bears full responsibility. It discloses auto-casting behavior and error handling (failure returns allowed values in error message), and hints at preconditions. However, it does not mention side effects (e.g., implicit changes to dependent features), persistence of settings, or whether the tool requires an active connection. The disclosure is adequate but not comprehensive.

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 reasonably concise, with a short introduction followed by behavior details and parameter documentation. The inclusion of an example in the precondition section adds clarity without excessive length. Minor redundancy (e.g., '설정한다' and '설정에 실패하면' could be tighter) but overall well-structured.

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 output schema exists, return values are covered externally. The description covers parameter semantics, failure behavior, and preconditions, which are the main contextual needs for a setter tool with two required parameters. One could argue it should mention that a connected camera is implied, but since sibling tools include connect/disconnect, it's reasonably complete.

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?

With 0% schema description coverage, the description must fully explain parameters. It does so for both 'name' (GenICam feature name) and 'value' (number/string/boolean), adding typing info beyond the schema's minimal type definition. While it could be more detailed (e.g., valid ranges for common features), it provides solid semantics for an AI agent to use the tool correctly.

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 sets GenICam feature values (노출·게인·트리거·픽셀포맷·ROI 등), with specific verb '설정한다' and resource 'GenICam feature'. It distinguishes from sibling tools like list_features, get_feature, and grab by focusing on setting, not reading or listing. Examples further clarify scope.

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 guidance on when to use this tool by mentioning auto-casting of values and error messages containing allowed ranges if setting fails. It includes a concrete example of a precondition (ExposureAuto must be 'Off' to set ExposureTime), which helps agents avoid common pitfalls. However, it lacks explicit when-not-to-use or alternatives beyond precondition context.

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