validate

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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly states that the tool returns both source files and syntax check results, and that the agent must perform the structural comparison. It also lists the exact return fields, which is valuable behavioral context, though it does not cover error handling or side effects.

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 concise, front-loaded with the main purpose, and uses a clear Args/Returns structure. Every sentence earns its place, and there is no fluff or 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?

The description provides all necessary context for the agent to understand what the tool does, what inputs to provide, and what outputs to expect. It also explicitly assigns the responsibility of structural comparison to the agent, which is critical for correct usage. The presence of an output schema reduces the need for more return-value detail.

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?

The schema provides only type 'string' for both parameters with no descriptions, but the description adds crucial semantics by stating each is a 'Path or inline content' for the original DAG and the generated flow. This fully compensates for the 0% schema description coverage.

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 opens with a specific verb and resource: 'Validate a converted Prefect flow against the original Airflow DAG.' This clearly distinguishes the tool from siblings like 'read_dag' and 'scaffold', and states the exact scope of the operation.

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 clearly implies when to use the tool (when validating a converted flow against its original DAG) and instructs the agent on the next step: 'You perform the structural comparison.' However, it does not explicitly mention alternatives or when not to use this tool, so it stays just below a perfect score.

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