ncloud_dataflow_verify_job

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

The readOnlyHint annotation already informs the agent this is a safe, read-only operation. The description adds context that it validates job configuration without modifying state, which is consistent. It does not contradict annotations. However, it does not elaborate on any additional behavioral traits beyond validation.

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 highly concise—two short sentences that convey the action and its purpose. It is front-loaded with the key verb and resource. Every word is necessary and there is no redundancy.

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 has one parameter and no output schema, the description adequately covers what it does and when to use it. It mentions validation before running and configuration checking. It could optionally describe the return format (e.g., success/failure or error details), but overall it's complete enough for the agent to understand its role among many Data Flow sibling tools.

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 input schema already provides a description for the single parameter (jobId: 'Job ID to verify'). Schema coverage is 100%, so the baseline is 3. The tool description does not add further meaning or context for the parameter beyond what the schema provides.

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 purpose: 'Verify (validate) a Data Flow job's execution request items before running. Checks if the job configuration is valid.' It uses a specific verb ('Verify') and identifies the resource ('Data Flow job's execution request items'). It distinguishes from siblings like execute_job (which runs the job) and get_job (which retrieves details).

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 usage before running a job ('before running'). It gives clear context for when to use this tool—to validate configuration prior to execution. However, it does not explicitly state when not to use it or provide alternatives, but the context is sufficient given the tool's narrow scope.

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