Checks whether a tool's sample output matches an expected type such as object, array, string, number, boolean, or null. Use it to catch output-type mismatches before running workflows.
Validates tool output type against expectation
| Name | Required | Description | Default |
|---|---|---|---|
| sample_output | Yes | ||
| expected_output_type | No |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not say whether validation is a pure read, what happens on a mismatch (error vs. boolean result), or what the response looks like, which matters for a validation tool whose entire value is its verdict.
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?
A single short sentence is front-loaded and wastes no words. It is terse to the point of under-specification, but structurally there is nothing superfluous to trim.
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 tool is simple (2 params, one enum), but with no annotations, no output schema, and 0% parameter coverage, the description leaves the return semantics and mismatch behavior entirely undefined. An agent cannot confidently predict what calling it produces.
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 both parameters, so the description must compensate. 'output type against expectation' loosely hints that sample_output pairs with expected_output_type, but it never explains the expected type domain or whether sample_output is a value, a type string, or a serialized payload.
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 (validates) and the subject (tool output type against an expectation), so the general intent is inferable. However, 'expectation' is vague and it does nothing to distinguish itself from the closely related sibling inspect_node_output_shape, leaving the agent to guess which check tool to use.
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 indication of when this tool should be invoked versus alternatives such as inspect_node_output_shape or replay_sample_payload, nor any preconditions. The agent gets no routing guidance at all.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.