Patient demographics, injury history, and medications for a rehab case. Free — evaluate case relevance before purchasing biomechanical reports for insurance_claim_validation or PT_outcome_measurement.
| Name | Required | Description | Default |
|---|---|---|---|
| case_path | Yes | Case path, e.g. 'PhysicalRehab/40-50/Male/LabrumTear' |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses that the tool is 'Free' and intended for pre-purchase evaluation, which adds some behavioral context. However, it does not mention response format, data completeness, or any operational limitations, leaving room for additional disclosure.
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, concise sentence that front-loads the primary content and use case. Every word adds value, with no redundancy or filler.
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?
Given this is a simple get operation with one parameter and no output schema, the description sufficiently covers the tool's purpose, content, and usage context. It could mention the return format, but that is not critical for a free evaluation profile. The description is complete enough for an agent to select and invoke this tool appropriately.
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 schema description covers 100% of parameters, providing a clear example for case_path. The tool description adds general context about the content (demographics, injury history, medications) but does not elaborate on parameter-specific semantics beyond what the schema already offers, aligning with the baseline.
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 clearly states the tool returns patient demographics, injury history, and medications for a rehab case. It differentiates from sibling tools by highlighting it is free and used for evaluating case relevance before purchasing reports, making the purpose unambiguous.
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 explicitly instructs when to use this tool: 'evaluate case relevance before purchasing biomechanical reports' and specifies the use cases (insurance_claim_validation, PT_outcome_measurement). It does not directly name alternative sibling tools, but the context implies its role as a preliminary assessment, which is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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