Ops MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's automated workflow (steps 1-6), including that it reads logs and extracts IDs, which clarifies its read-only, analytical nature. However, it lacks details on potential side effects, error handling, or performance characteristics like rate limits, leaving some behavioral aspects unclear.

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 efficiently structured with a clear purpose statement, a numbered list of automated steps, and separate sections for arguments and returns. Every sentence adds value, such as the sibling tool comparison and parameter warnings, with no redundant or verbose content, making it highly readable and informative.

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?

For a complex diagnostic tool with 3 parameters, 0% schema coverage, no annotations, but an output schema, the description is complete. It covers the tool's purpose, usage guidelines, parameter semantics, and behavioral workflow. Since an output schema exists, it appropriately omits detailed return value explanations, focusing on the 'comprehensive failure report with root cause analysis.'

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?

Given 0% schema description coverage, the description fully compensates by explaining all three parameters: 'dag_id' is described with an example, 'env' specifies allowed values and critical usage instructions, and 'date' clarifies format and default behavior. This adds essential meaning beyond the bare schema, ensuring parameters are well-understood.

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 explicitly states the tool's purpose as 'One-shot diagnosis of a failed DAG run' and details the six specific automated steps it performs. It clearly distinguishes this from sibling tools by noting it 'replaces the need to call 5-6 tools manually,' making its comprehensive diagnostic function distinct from simpler tools like get_dag_run_details or get_task_log.

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 explicit guidance on when to use this tool versus alternatives: it should be used for comprehensive failure analysis instead of manually calling multiple tools. It also includes important usage constraints, such as the warning not to guess or default the 'env' parameter and to ask the user if unspecified, ensuring correct application.

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