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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'Checks' coverage, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns detailed or summary information, or handles errors. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy for an agent to parse quickly and understand the core function.

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 complexity of checking Medicare coverage, the lack of annotations and output schema, and the description's minimal detail, it's incomplete. It doesn't explain what the return value includes (e.g., coverage details, limitations, or next steps), which is crucial for a tool with no output schema, leaving the agent uncertain about the result format.

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, clearly documenting all three parameters (insuranceType, state, treatmentCode) with their types and purposes. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score without compensating or enhancing the schema's information.

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 ('Checks') and resource ('what treatments and procedures are covered by Medicare'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'find_nearby_medical_facilities' or 'get_emergency_contacts', which serve different healthcare-related functions, so it doesn't reach the highest score.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or how it relates to sibling tools such as 'schedule_emergency_transport' or 'sequentialthinking', leaving the agent to infer usage context without explicit direction.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'finds' and 'match specific requirements,' implying a read-only search operation, but fails to disclose critical traits: whether it requires authentication, rate limits, data freshness, error handling, or what the output format looks like (no output schema exists). For a tool with 7 parameters and no annotations, this is a significant gap in transparency.

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, efficient sentence that front-loads the core purpose without unnecessary details. It wastes no words, making it appropriately concise. However, it could be slightly improved by structuring usage hints, but as-is, it's well-sized for its purpose.

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 complexity (7 parameters, no annotations, no output schema), the description is incomplete. It doesn't address behavioral aspects like authentication or rate limits, lacks output details, and provides no usage context. While the schema covers parameters well, the overall context for an AI agent to use this tool effectively is insufficient, especially for a search tool with multiple filters and no safety annotations.

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 description adds minimal value beyond the input schema, which has 100% coverage with detailed parameter descriptions and enums. It mentions 'specific requirements,' hinting at parameters like 'careQuality' or 'treatmentNeeds,' but doesn't explain their semantics or relationships. With high schema coverage, the baseline is 3, as the schema does the heavy lifting, and the description doesn't compensate with additional insights.

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: 'Finds hospitals and clinics nearby user location that match specific requirements.' It specifies the verb ('finds'), resource ('hospitals and clinics'), and scope ('nearby user location'), distinguishing it from siblings like 'check_medicare_coverage' or 'schedule_emergency_transport.' However, it doesn't explicitly differentiate from all siblings (e.g., 'get_emergency_contacts' might also involve medical facilities), so it's not a perfect 5.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when-not scenarios (e.g., for non-medical emergencies or when insurance coverage is the primary concern) or explicitly refer to sibling tools like 'check_medicare_coverage' for coverage checks. Usage is implied by the purpose but lacks explicit context, scoring low due to the absence of clear alternatives or exclusions.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Retrieves', implying a read-only operation, but doesn't cover aspects like authentication needs, rate limits, error handling, or what the return format looks like. This leaves significant gaps for a tool with no annotation coverage.

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, efficient sentence that directly states the tool's purpose without any redundant or unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the retrieved information includes, how it's formatted, or any behavioral traits like permissions or limitations. For a tool with no structured support, this leaves the agent under-informed.

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 coverage is 100%, with clear descriptions for both parameters ('location' and 'serviceType'), so the schema does the heavy lifting. The description adds no additional semantic context beyond implying the parameters are used for filtering, which aligns with the schema but doesn't provide extra value.

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 verb ('Retrieves') and resource ('emergency contact information') with a specific scope ('for a specific location'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'find_nearby_medical_facilities' or 'schedule_emergency_transport', which might also involve emergency services, so it doesn't reach the highest score.

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 provides no guidance on when to use this tool versus alternatives such as the sibling tools. It mentions 'specific location' but doesn't specify prerequisites, exclusions, or contexts where this tool is preferred over others, leaving the agent with minimal usage direction.

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?

With no annotations provided, the description carries full burden for behavioral disclosure. 'Arranges' implies a write/mutation operation, but the description doesn't specify whether this triggers actual transportation, requires authorization, has side effects, or what happens after arrangement. This is inadequate for a tool that appears to perform a critical action.

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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a tool with clear parameters documented elsewhere.

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 tool that appears to perform a critical emergency action with no annotations and no output schema, the description is insufficient. It doesn't explain what 'arranges' means operationally, what confirmation or response to expect, or any constraints or requirements beyond the basic parameters documented in the schema.

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, so all parameters are documented in the schema itself. The description doesn't add any parameter-specific information beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

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 action ('arranges') and resource ('emergency medical transportation'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling tools like 'check_medicare_coverage' or 'find_nearby_medical_facilities' that might also relate to emergency medical services.

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 provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, constraints, or how it differs from sibling tools like 'get_emergency_contacts' or 'sequentialthinking' that might be relevant in emergency medical situations.

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?

No annotations are provided, so the description carries full burden. It discloses key behavioral traits like adaptability ('can adjust total_thoughts'), revision capabilities ('question or revise previous medical assessments'), and iterative nature ('Repeats the process until a satisfactory diagnosis'). However, it lacks details on error handling, performance limits, or authentication needs, leaving gaps for a tool with 9 parameters.

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 front-loaded with purpose and usage guidelines, but becomes verbose in 'Key features' with repetitive points (e.g., multiple lines on revision and branching). Sentences like 'Generates a clinical hypothesis' and 'Verifies the hypothesis' could be condensed. Overall, it's informative but could be more streamlined.

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 no annotations and no output schema, the description provides good usage context and behavioral hints. However, for a complex tool with 9 parameters involving medical decision-making, it lacks details on output format, error cases, or security considerations, making it incomplete for full agent understanding.

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 100%, so parameters are well-documented in the schema. The description adds minimal semantic context beyond the schema, such as implying 'total_thoughts' is adjustable and 'thought' represents 'clinical thinking step,' but doesn't elaborate on parameter interactions or usage examples. Baseline 3 is appropriate as the schema does the heavy lifting.

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 enables 'dynamic and reflective medical problem-solving through thoughts' and 'helps analyze medical problems through a flexible thinking process.' It specifies the domain (medical) and core function (problem-solving via sequential thoughts). However, it doesn't explicitly differentiate from sibling tools like 'check_medicare_coverage' or 'find_nearby_medical_facilities,' which serve different purposes rather than overlapping in medical analysis.

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 provides explicit 'When to use this tool' guidance with seven specific scenarios, such as 'Breaking down complex medical problems into steps' and 'Clinical analysis that might need course correction.' It clearly outlines appropriate contexts without mentioning alternatives, which is sufficient given the siblings are unrelated (e.g., coverage checks, facility finding).

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