연결 진단

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

With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It says the tool 'checks' settings/registry and 'tests' API calls, but does not state whether these are read-only operations, whether the API call test can cause side effects, or what constitutes a successful/failed check. This lack of detail is significant for a tool that might execute actual calls.

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 is concise and front-loaded with the core action ('checks'), followed by optional behavior. It contains no redundancies or filler, making it appropriately compact for the information it conveys.

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 tool's nested schema with required fields (probe.datasetId, probe.operation) and absence of output schema or annotations, the description is too sparse. It does not explain the purpose of the probe object, expected return values, or error handling. This leaves significant gaps for the agent to use the tool correctly.

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 must compensate by explaining parameter meaning. However, it does not mention any parameter names or describe datasetId, operation, or params. The only hint is the word 'probe' in the schema, which aligns with the tool's testing action, but the field semantics remain completely unexplained.

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's specific diagnostic actions: checking service key settings ('서비스키 설정'), registry status ('레지스트리 상태'), and optionally testing actual API calls ('선택적으로 실제 API 호출을 시험'). This distinguishes it from siblings like execute_operation and discover_datasets, which have different purposes.

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 gives no explicit guidance on when to use this tool versus alternatives. It neither mentions siblings nor provides exclusions or specific use cases. The optional API call testing is implied as a diagnostic feature, but there is no clear 'when to use' or 'when not to use' direction.

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