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 only restates the purpose and does not reveal additional traits such as whether the tool is read-only, what specific outputs are generated, or any side effects. Minimal behavioral insight is offered beyond the name.

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 immediately communicates the tool's function. No unnecessary words or repetition, making it well-structured and appropriately sized.

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 presence of a fully described schema and an output schema reduces the need for explanation of parameters and return values. However, the description lacks usage guidelines and behavioral context, which are important given the existence of sibling tools. The tool is simple enough that this is a minor gap, but not a complete picture.

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 fully describes all three parameters (100% coverage), so the baseline is 3. The description adds no additional parameter semantics, but since the schema already provides complete meaning for each parameter, this is not a drawback.

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 ('Analyze') with a clear resource ('insurance policy clauses') and a defined outcome ('identify key terms'). It clearly differentiates from sibling tools like assess_insurance_risk and compare_insurance_policies, which target different aspects of insurance processing.

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?

No guidance is provided on when to use this tool versus the alternatives. The description lacks any mention of use cases, exclusions, or complementary relationships with sibling tools, leaving the agent to rely solely on the tool name.

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 the full burden of disclosing behavior. It only states the general purpose ('assess risks, provide premium estimates') without describing side effects, required permissions, whether the operation is read-only, or any output details beyond what the schema might imply.

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 communicates the tool's core function without extraneous words. It is front-loaded and easy to parse.

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?

While the schema and output schema provide technical details, the description lacks contextual completeness. It doesn't mention when to use this tool in an insurance workflow, what data is expected beyond the schema, or how it compares to sibling tools. For a tool with moderate complexity, this is adequate but has clear gaps.

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 descriptive text for all three parameters (risk_data, jurisdiction, insurance_type), covering 100% of parameters. The description adds no additional parameter-level detail, so the baseline of 3 applies because 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's function: 'Assess insurance risks and provide premium estimates.' This distinguishes it from sibling tools like analyze_policy_clauses or generate_claim_report, which focus on different aspects of insurance processing.

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 does not mention scenarios, prerequisites, or exclusions. For example, it doesn't explain that this is for risk/price evaluation rather than clause analysis or claim generation.

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 for behavioral disclosure. It only says it compares and identifies 'best value' without explaining how that determination is made, what limitations exist, or what the user should expect regarding input handling or output semantics. This is a significant gap for a tool with no annotation support.

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, front-loaded sentence that states the core purpose concisely. No wasted words or redundant information; it earns its place and is easily scannable.

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 comparison tool with an output schema, the description covers the essential purpose but lacks context on selection criteria and behavioral details. The presence of sibling tools and no annotations increases the need for richer description, which is only partially met. Overall, it is minimally adequate but leaves gaps in usage guidance and method transparency.

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 all four parameters, so the schema already explains each parameter clearly. The description adds no additional parameter-level meaning, but the schema's coverage justifies a baseline score of 3.

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 specifies a verb ('Compare'), a resource ('insurance policies'), and an outcome ('identify best value'). It is distinct from sibling tools like analyze_policy_clauses, which focuses on detailed clause analysis, and assess_insurance_risk, which assesses risk.

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?

Usage is implied by the core action of comparing policies, but there is no explicit guidance on when to choose this tool over alternatives. For example, it does not mention that analyze_policy_clauses should be used for clause-level analysis, or that assess_insurance_risk is for risk assessment. The description provides no exclusions or alternative recommendations.

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 must disclose behavioral traits, but it only says 'generate' without indicating whether the operation is read-only, whether it modifies data, or what the report's structure is. The existence of an output schema is not mentioned, leaving the agent without essential safety information.

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 short sentence, which is concise, but it adds little beyond the tool name and lacks useful structure. It is not verbose, yet the information is minimal and doesn't fully earn its place.

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?

Despite having an output schema and sibling tools, the description provides minimal context. It doesn't explain how inputs are used, what 'comprehensive' means, or when to choose this over assess_insurance_risk. The tool has a nested object and multiple parameters, yet the description is under-specified.

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 provides full descriptions for all three parameters (claim_data, policy_text, insurance_type), reaching 100% coverage. The description adds no additional parameter semantics, but since the schema already handles this, a baseline score of 3 is appropriate.

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 states a clear action ('Generate') and a specific resource ('comprehensive insurance claim report'), distinguishing it from sibling tools like analyze_policy_clauses and assess_insurance_risk which focus on analysis and risk assessment. However, 'comprehensive' is vague and doesn't specify what the report includes.

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?

There is no guidance on when to use this tool versus alternatives such as compare_insurance_policies or assess_insurance_risk. It doesn't mention prerequisites, typical scenarios, or 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.