airflow_get_dag

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

Annotations already indicate read-only and idempotent. Description adds valuable details: auto-resolution of ui_url, return structure (dag, ui_url, request_id), and error format (compact JSON payload). No contradictions.

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?

Highly concise with clear sections: purpose, parameter instructions, returns, and errors. Every sentence adds value; no fluff.

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?

Covers key aspects: purpose, parameter behavior, return format, errors. Output schema exists so detailed object description is unnecessary. Could mention authentication/network requirements but those are implicit for Airflow 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?

Schema coverage is 0%, but description compensates fully: explains conditional requirement (dag_id needed only with instance) and auto-resolution behavior of ui_url. Adds clarity beyond schema.

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?

Clearly states 'Get DAG details and a UI link,' specifying the verb and resource. Distinguishes from sibling tools like airflow_list_dags (list vs get) and airflow_get_dag_run (different resource).

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?

Provides parameter guidance (provide one of instance/ui_url, dag_id required with instance) but lacks explicit when-to-use vs alternatives like airflow_list_dags or airflow_get_dag_run. Usage context is implied but not fully articulated.

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