Explains class unsatisfiability by generating a trace of logical contradictions via DL tableaux reasoning. Shows why the class cannot be instantiated.
Explain why a class is unsatisfiable using DL tableaux reasoning. Returns an explanation trace showing the logical contradictions that make the class impossible to instantiate.
| Name | Required | Description | Default |
|---|---|---|---|
| class_iri | Yes | IRI of the class to explain unsatisfiability for |
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 must fully disclose behavior. It states that the tool returns an explanation trace, but it does not mention whether the tool is read-only, requires authentication, or has any side effects. The description is minimal and lacks details about error handling or prerequisites.
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 concise, consisting of two sentences that front-load the core purpose and output. Every word adds value, and there is no extraneous information.
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 a simple single-parameter interface with no output schema. The description covers the core functionality and output, but it does not mention that the class must be unsatisfiable for the tool to produce meaningful output, nor does it explain error scenarios. It is adequate but not thorough.
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 input schema has 100% description coverage for the single parameter 'class_iri', already describing it as 'IRI of the class to explain unsatisfiability for.' The description adds no additional semantic value beyond the schema, so baseline score of 3 applies.
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 explicitly states the tool's purpose: 'Explain why a class is unsatisfiable using DL tableaux reasoning.' It also describes the output as 'an explanation trace showing the logical contradictions.' This clearly distinguishes it from siblings like onto_dl_check, which likely checks satisfiability without explanation.
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 indicates when to use the tool (to explain unsatisfiability) but does not provide guidance on when not to use it or what alternatives exist. For instance, if the class is satisfiable, this tool may not be applicable, but that is not mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.