inspect_node_output_shape

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Inspects' implies a read-only operation, but there is no mention of permissions, side effects, output format, or what happens with malformed sample_output.

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 a single, front-loaded sentence with no wasted words. Its brevity is appropriate, though the same brevity contributes to gaps captured in other dimensions.

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?

For a tool with an empty parameter schema, no annotations, and no output schema, the description is too thin. An agent lacks enough detail about input expectations, return shape, and intended usage context to invoke the tool reliably.

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 single parameter sample_output has no schema description, no type, and no constraints, while the description only loosely refers to a 'node sample'. It does not compensate for the 0% schema coverage by explaining what sample_output should contain or what format it expects.

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 a verb and a resource ('Inspects output type shape'), but it largely restates the tool name and does not clarify what 'output type shape' means in practice or how it differs from siblings like derive_tool_schema or validate_tool_io. It is minimally informative but not distinct enough for confident selection.

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 guidance on when to use this tool versus alternatives. Sibling tools such as derive_tool_schema and validate_tool_io appear related, yet the description provides no context, prerequisites, or exclusion criteria.

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