Classify any string, object, or list into a caller-defined label by asking a question with labeled options. Resolve ambiguous states by selecting the most appropriate label based on your criteria.
Choose one caller-defined label for string, object, or list state.
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes | ||
| options | Yes | ||
| question | Yes | ||
| logging_exclusions | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It does not state whether the operation is read-only, whether it has side effects, how it handles invalid states, or what the output format is. The minimal description leaves the agent guessing about the tool's behavior.
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 extremely brief (one sentence), but this brevity is not effective conciseness—it is under-specification. It front-loads the core idea but omits critical details needed for correct usage. A good concise description would pack more actionable information into a few sentences.
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 has 4 parameters, nested objects, no annotations, and an output schema that is not described in the definition. The description does not explain the purpose of each parameter, the expected output, or any edge cases. Given the complexity, the description is grossly inadequate for an agent to invoke the tool correctly.
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%, so the description must compensate by explaining the parameters. It does not mention 'question', 'options', or 'logging_exclusions' at all. The only hint is 'caller-defined label', which loosely relates to 'options', but no parameter semantics are clarified. The description fails to aid in parameter understanding.
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 the core action ('choose one caller-defined label') and the input type ('string, object, or list state'), which gives a general sense of classification. However, it does not clarify what 'label' means, how it relates to 'options', or how it differs from the sibling tools (jev_check, jev_score, etc.). It is more than a tautology but remains vague.
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. It does not mention contexts where classification is preferred over scoring or evaluation, nor any exclusions or prerequisites. The agent is left to infer the appropriate usage from the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.