Retrieve execution time statistics for Naver Cloud Data Flow jobs within a date range to monitor performance and diagnose scheduling issues.
Get job execution time statistics for Data Flow dashboard.
| Name | Required | Description | Default |
|---|---|---|---|
| endDate | Yes | End of the query range (ISO 8601, e.g. 2025-03-20T23:59:59) (required) | |
| startDate | Yes | Start of the query range (ISO 8601, e.g. 2025-03-19T00:00:00) (required) |
Changes observed during successful MCP inspections.
v2.0.1Input schema / properties / endDateAdded value: +{
+ "description": "End of the query range (ISO 8601, e.g. 2025-03-20T23:59:59) (required)",
+ "type": "string"
+}Input schema / properties / endTimeRemoved value: -{
- "description": "End time for query range (ISO 8601 format)",
- "type": "string"
-}Input schema / properties / startDateAdded value: +{
+ "description": "Start of the query range (ISO 8601, e.g. 2025-03-19T00:00:00) (required)",
+ "type": "string"
+}Input schema / properties / startTimeRemoved value: -{
- "description": "Start time for query range (ISO 8601 format)",
- "type": "string"
-}Input schema / requiredAdded value: +[
+ "startDate",
+ "endDate"
+]v1.10.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the bar is lower, but the description adds essentially no behavioral context beyond the purpose statement. It discloses nothing about aggregation granularity, return structure, or pagination even though 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?
A single front-loaded sentence with zero filler. It is efficient, though arguably under-sized for the scope of a statistics-returning tool.
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?
With no output schema and no annotation detail beyond readOnlyHint, the description should explain what these execution-time statistics contain. It does not, leaving an agent unable to anticipate the return values.
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 100%, so both startDate and endDate are fully documented in the schema. The description adds no format or interpretation detail beyond that, which is the expected baseline when the schema carries the parameter semantics.
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?
States a specific verb (Get) and resource (job execution time statistics), distinguishing it somewhat from siblings like get_execution_interval and get_execution_result. However, 'statistics' remains vague about exactly what is returned, and it doesn't explicitly contrast with the closest siblings.
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 when-to-use guidance, prerequisites, or alternatives. Saying it is 'for Data Flow dashboard' hints at context but does not tell an agent when to pick this over get_execution_interval, get_execution_result, or get_job_executions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.