Medicare Enrollment and Revalidation Data

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds substantial context: it enumerates the returned data (due date or TBD, source metadata, explicit submission-status limits, handoffs), emphasizes it is 'free read-only', lists prohibited actions, and notes invalid NPIs are handled as invalid results. There is no contradiction with 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 three sentences: the first states purpose, the second lists outputs, and the third lists limitations. Every sentence provides distinct value with no redundancy. It is front-loaded with the core action and remains appropriately sized for the tool's complexity.

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?

With no output schema, the description fully explains what the tool returns (matching enrollment, due date/TBD, source metadata, limits, handoffs). It also covers the read-only nature, free access, and prohibitions. The schema's invalid NPI behavior complements the description. This is complete enough 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?

The only parameter 'npis' has comprehensive schema description coverage (format, bounds 1-100, uniqueness, invalid-digit handling). The description adds no new parameter-level information beyond echoing 'up to 100 NPIs'. Baseline 3 is appropriate since the schema carries the semantic burden.

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 opens with the specific verb 'Check' and the resource 'current public CMS Medicare Revalidation List'. It enumerates distinct outputs (matching enrollment, due date/TBD, source metadata, submission-status limits, handoffs), clearly distinguishing it from sibling tools like 'get_medicare_revalidation_automation_offer' and 'get_medicare_roster_watch_offer', which focus on offers/previews.

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 does not explicitly name alternative tools, but it clearly states the tool's scope and limitations ('cannot open PECOS, submit a revalidation, start a paid run, open checkout, or purchase anything'), effectively telling the agent when not to use it. This provides clear context for decision-making without naming siblings.

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 read-only, idempotent, open-world, and non-destructive hints. The description adds meaningful behavioral context beyond this: it cannot authenticate, create tasks, start runs, or purchase, and it requires explicit user confirmation before any separate paid action. This transparently sets expectations for agent 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 two sentences with dense, front-loaded information. The first sentence enumerates the exact deliverables, and the second sentence provides the behavioral boundary. No words are wasted, and all content contributes to understanding.

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?

For a parameter-free, read-only informational tool with no output schema, the description is complete. It specifies the exact return contents, clarifies its non-executable nature, and provides actionable guidance for the agent. No critical information is missing.

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, giving a baseline of 4. The description correctly focuses on output content rather than parameter details, and no parameter documentation is needed because the schema is empty and 100% covered by the absence of parameters.

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 ('Return') and explicitly enumerates the exact resource and contents: $0.01-per-returned-NPI price, 100-NPI limit, Apify Store and MCP paths, buyer-paid condition, templates, and fulfillment expectation. This clearly distinguishes it from sibling tools focused on due dates, roster watch, or behavioral health previews.

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 clearly states when to use the tool ('informational read-only') and what it cannot do (authenticate, create task, start run, purchase), and it directs the agent to require user confirmation before separate paid actions. However, it does not explicitly name alternative sibling tools for those paid/actionable operations, so it falls short of full alternative 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?

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false), the description adds meaningful behavioral context: it cannot trigger checkout/purchase, requires user confirmation, and discloses public-source limitations and automatic-fulfillment expectations. This goes well beyond what the annotations alone provide.

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 two sentences are tightly packed yet highly readable. The first sentence enumerates the offer details in a compact list, and the second sentence provides usage constraints. No filler or redundancy.

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 there is no output schema, the description carries the full burden of explaining what is returned and how to act. It covers the offer's key attributes (price, scope, delivery, limitations, paths, expectations) and the required interaction pattern (confirmation before purchase). This is complete for the tool's complexity.

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, so per rubric the baseline is 4. The description does not need to explain any input schema details, and the no-parameter setup is fully covered by the schema.

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 the specific verb 'Return' and lists the exact components of the offer: price, NPI scope, delivery, limitations, checkout/cancellation paths, and fulfillment expectations. This makes the tool's purpose unmistakable and clearly distinguishes it as an informational offer tool rather than an action tool.

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 clearly states that this tool is read-only and cannot open checkout, subscribe, or purchase, and instructs the user to require explicit confirmation before separate purchase actions. However, it does not explicitly name or contrast sibling tools (e.g., get_medicare_revalidation_automation_offer), so cross-tool guidance is missing.

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?

Beyond the readOnlyHint annotation, the description discloses important behavioral boundaries: it cannot start Apify runs, open checkout, contact applicants, or purchase anything. It also describes the output as 'validated' and includes 'limitations,' adding meaningful behavioral context beyond what annotations provide.

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 concise, front-loaded with the primary purpose, and the second sentence adds necessary exclusions. No words are wasted, and it remains readable despite the complex subject matter.

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 has only one optional parameter, no output schema, and rich annotations, the description is complete enough: it states what data is returned (10-row preview, source dates, national counts, limitations) and clarifies the optional handoff. It covers all needed invocation context.

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 sole parameter 'states' is already fully documented in the input schema with a clear description. The tool description adds no additional semantics about the parameter, so the 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 uses a specific verb ('Return') and clearly identifies the resource: a current validated 10-row public preview of behavioral-health NPIs in CMS pending first-time Medicare enrollment files. This distinguishes it from the sibling tools, which focus on revalidation due dates and purchase offers.

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 not to use this tool: 'cannot start an Apify run, open checkout, contact applicants, or purchase anything.' This gives clear exclusions, but it does not name alternative tools for those actions, so it stops short of full guidance.

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