Apache Airflow MCP Server

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

The description adds some behavioral context beyond what annotations provide. Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, repeatable read operation. The description adds useful context about the return format and the limit parameter's coercion behavior, but doesn't mention pagination, error conditions, or authentication requirements.

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 well-structured with clear sections for the purpose, parameters, and returns. Each sentence adds value, though the parameter documentation could be slightly more concise. The information is front-loaded with the core purpose stated first, followed by necessary details.

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 moderate complexity (4 parameters, read-only operation) and the presence of both comprehensive annotations and an output schema, the description provides sufficient context. It explains all parameters thoroughly and documents the return structure, though it could benefit from more usage context and error handling information.

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 carries the full burden of parameter documentation. It provides clear explanations for all 4 parameters, including which are optional/required, default values, and specific behavioral details like 'coerced to non-negative int, fractional values truncated' for the limit parameter. This compensates well for the lack of schema descriptions.

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 as 'List dataset events' which is a specific verb+resource combination. It distinguishes itself from siblings like airflow_list_dags or airflow_list_dag_runs by focusing specifically on dataset events rather than DAGs or runs. However, it doesn't explicitly contrast with all possible alternatives in the sibling list.

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 no guidance on when to use this tool versus alternatives. While it's clear this is for listing dataset events, there's no mention of when dataset events should be queried versus other event types, what prerequisites might exist, or how this relates to other dataset-related operations that might exist in the broader system.

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