list_import_errors

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

Annotations already provide readOnlyHint=true, so the description adds value by specifying the output includes filename and stack trace. It does not contradict annotations and provides behavioral context for what the tool returns.

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?

Two sentences, front-loaded with the verb 'List' and the resource 'DAG import errors'. Every sentence earns its place, with no wasted words. Highly efficient.

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 simplicity (list operation, optional pagination params), the description explains the purpose, output content, and typical use case. An output schema exists, so return values are not needed in description. Missing details about pagination are implicit. Generally complete.

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% for the two parameters (limit, offset). The description does not mention these parameters at all, so it adds no semantic meaning beyond the schema. For a tool with 2 parameters, the description should compensate for the lack of schema descriptions, but it fails to do so.

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?

Description clearly states it lists DAG import errors (parse failures) with filename and stack trace. It also provides the specific use case: finding why a DAG is missing or broken. This distinguishes it from sibling tools like get_dag or list_dags.

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?

Description says 'The quickest way to find why a DAG is missing from the list or broken', which gives clear context for when to use this tool. However, it does not explicitly state when not to use it or mention alternatives, but the context is strong.

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