CarePlanKit — Nursing Care Plans

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

The description discloses the content structure and includes an educational disclaimer ('not medical advice'), adding behavioral context beyond the annotations. Annotations already declare readOnlyHint and idempotentHint true, so the description does not need to restate safety. It does not mention edge cases or error behavior, but the core behavioral traits are well covered.

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 three sentences long, front-loaded with the tool's purpose and content, then audience and usage guidance. Every sentence adds meaningful information, 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 the single parameter, no output schema, and strong annotations, the description is sufficiently complete. It explains the return content, the intended user, when to use it, and the educational limitation. The sibling tool context does not demand further clarification.

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 already provides a clear description of the 'condition' parameter with examples. The description adds further examples (sepsis, CHF, COPD, diabetes, pneumonia) in the usage context, reinforcing the expected values. Since schema coverage is 100%, the baseline is 3, and the extra examples elevate it to 4.

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's purpose with a specific verb ('Get') and resource ('nursing care plan'), and enumerates the exact components (diagnoses, goals, interventions, sources). It distinguishes itself from the sibling tool 'list_nursing_conditions' by focusing on generating a care plan for a specific condition rather than listing conditions.

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 states when to use the tool ('Use when a nursing student asks for a care plan, nursing diagnoses, interventions or goals') and provides examples. However, it does not explicitly mention when not to use it or name alternatives beyond the sibling tool, so it lacks full exclusion guidance.

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

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, covering safety and predictability. The description adds the meaningful constraint 'with available nursing care plans', which clarifies the result includes only conditions that have care plans, not all conditions. This is useful beyond annotations.

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 two sentences with no redundancy. The first sentence states the core purpose, and the second provides usage context. Every word contributes meaning.

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 the tool's simplicity (no params, no output schema, strong annotations), the description is complete. It tells the agent what the tool returns (a list of conditions) and when to use it. The lack of an output schema is not a problem because the description implies the return type.

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 tool has zero parameters, and schema coverage is 100% (empty object). The description does not need to explain parameters, and the baseline for 0 params is 4. No additional parameter information is required.

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 uses a specific verb 'List' with a clear resource 'conditions with available nursing care plans'. It clearly distinguishes from the sibling tool get_nursing_care_plan, which retrieves a specific plan, by focusing on browsing all covered conditions.

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?

It explicitly states when to use the tool: 'Use when a nursing student asks what conditions are covered or wants to browse.' This provides practical context, though it does not mention the alternative get_nursing_care_plan or exclusion criteria, potentially leaving the agent to infer when not to use it.

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