list_dags

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

With no annotations, the description carries the burden. It explains key behaviors (missing import-error DAGs) and return structure, but does not explicitly state read-only or safe mutation behavior. The tool name 'list_' implies read-only, but a brief mention of non-destructive behavior would be ideal.

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: a concise first-line summary, a usage note, an Args block with clear parameter explanations, and a Returns block. Every sentence is informative without 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 sibling tools, the description clearly contrasts with get_import_errors. It fully describes the return fields and pagination. The moderate complexity is well-addressed, leaving no obvious gaps.

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 0%, so the description fully compensates by explaining each parameter: limit (max, default 100), offset (pagination), dag_id_pattern (case-insensitive substring filter), tags (list, filtering). This adds significant semantic value 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 states 'List DAGs registered in the cluster with their paused / import-error flags,' which is a specific verb (List) and resource (DAGs). It also clarifies the use case ('confirm a DAG parsed and registered'), distinguishing it from sibling tools like list_dag_runs or get_import_errors.

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 explicitly tells when not to use this tool: 'a DAG whose file fails to import ... does NOT appear here at all — call get_import_errors for that.' It provides a clear alternative (sibling tool) and a specific use case, making it easy to decide when to invoke.

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