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

The readOnlyHint annotation already establishes safety, but with no output schema, the description adds substantive value by enumerating the return contents: node modes, model options/defaults, allowed connections, and compose aspect ratios. It does not cover error behavior or specific usage constraints, so it stops short of a 5.

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 definition is a single, front-loaded sentence fragment that lists the key returned entities without filler. It is efficient, though the absence of a verb or lead-in makes it read more like a schema caption than a complete tool description.

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?

With no parameters, a readOnly annotation, and no output schema, the description carries the main burden of explaining what is returned—and it does so by listing the four main capability areas. It is adequate for a low-complexity read tool, though it could add context about when this capability data matters in the workflow lifecycle.

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 tool takes zero parameters, so there is nothing for semantics to clarify. Per the calibration rule, a zero-parameter tool has a baseline of 4, and the description appropriately adds no unnecessary parameter discussion.

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 names the specific content the tool returns—node modes, their models with options/defaults, allowed canvas connections, and compose aspect ratios—which makes the purpose concrete. It does not, however, distinguish this capabilities-discovery tool from workflow-related siblings like create_workflow or run_node, leaving the agent to infer that this is a read-only metadata tool.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives. The description is purely a content list; an agent gets no signal on when this tool should be called versus get_workflow or the other siblings.

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