bizinsured

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 successfully indicates the return values (class codes), but lacks information on whether this is a read-only operation, what happens when no matches are found, potential rate limits, or authentication requirements. Adequate but with clear 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?

Two sentences with zero waste: the first explains inputs/outputs and the second provides workflow positioning. Every word earns its place; the description is front-loaded with the core function and follows with usage guidance.

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 absence of an output schema, the description appropriately discloses the return values (class codes). With only two simple parameters and 100% schema coverage, the description successfully covers the tool's primary function and workflow role. Minor gap: does not address error handling or ambiguous input behavior.

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%, establishing a baseline of 3. The description adds the qualifier 'natural language' regarding the business_description parameter, which provides useful semantic context about the expected input format (free text vs. structured data), but this is a modest addition given the comprehensive 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 specific verbs ('takes' and 'returns') and clearly identifies the resource (business description) and output (NAICS, ISO GL, NCCI WC class codes). It distinguishes itself from sibling recommendation tools (get_carrier_recommendations, suggest_coverages) by explicitly positioning itself as the prerequisite step in the workflow.

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?

Provides explicit workflow guidance: 'Always call this first... before making recommendations.' This clearly defines when to use the tool relative to siblings and establishes it as a mandatory first step in the business classification workflow, effectively guiding the agent's tool selection sequence.

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 behavioral disclosure but fails to explain what 'handoff' means operationally (e.g., scheduling a call, creating a CRM ticket, transferring chat context), whether the operation is idempotent, or what data persistence occurs. The term 'generates' implies a write operation but lacks specifics on side effects.

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 with no redundant words. However, given the tool's complexity (nested objects, 5 parameters, business-critical handoff function), it may be overly terse rather than appropriately concise.

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 with complex input schema, no output schema, and no annotations, the description is insufficient. It omits expected return values, error conditions (e.g., what if no agents are available), and lacks explanation of the nested risk_profile structure which is critical for successful invocation.

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?

With 0% schema description coverage and a complex nested 'risk_profile' object containing 10 fields, the description provides no guidance on parameter meanings, formats, or relationships. It neither lists the required parameters (user_state, user_zip_code, risk_profile) nor explains the business logic of how these fields drive the matching algorithm.

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 phrase ('generates a handoff') and identifies the resource (matched independent agent) clearly. It distinguishes from siblings like 'classify_business' or 'get_carrier_recommendations' by focusing on human connection rather than automated processing or data retrieval.

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 like 'get_carrier_recommendations' or 'suggest_coverages'. It fails to mention prerequisites (e.g., whether classification should happen first) or when handoff is preferable to automated 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 carries full burden of behavioral disclosure. It adds value by specifying 'in plain language' (indicating simplification of technical jargon), but fails to disclose whether this is a read-only operation, if it requires specific permissions, or what output format to expect (string, object, etc.).

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?

Single sentence of nine words with no filler. The description is efficiently front-loaded and appropriately sized for the tool's apparent simplicity, though brevity comes at the cost of parameter documentation.

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 0% schema coverage, no output schema, and no annotations, the description is underspecified. It fails to document the 'business_context' parameter or indicate return value structure, leaving the agent without sufficient information to invoke the tool correctly without guessing parameter semantics.

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 0%, requiring the description to compensate. While 'coverage type' is implicitly referenced in the description text, 'business_context' (the optional second parameter) is completely undocumented. No guidance on valid values, formats, or when to provide the optional context is given.

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 'Explains a commercial insurance coverage type' using specific verb and resource. However, it does not explicitly differentiate from sibling 'suggest_coverages' (which could also involve explanatory content), leaving potential ambiguity about whether to use this for education vs. recommendation scenarios.

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 provided on when to use this tool versus alternatives like 'suggest_coverages' or 'classify_business'. There is no mention of prerequisites, conditions, or workflow positioning (e.g., use this after classification but before carrier selection).

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 behavioral disclosure. It mentions outputs are 'ranked' and include 'estimated premium ranges,' but fails to disclose whether this is a read-only lookup, if it generates a quote record, rate limits, or error conditions when no carriers match.

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 action. While appropriately sized for a simple tool, it is arguably too terse given the high parameter count and zero schema documentation.

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 14 undocumented parameters, no annotations, and no output schema, the description is insufficient. It does not explain the domain concepts (NAICS vs ISO codes), required vs optional fields, or the expected return structure beyond 'ranked carriers'.

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 has 0% description coverage across 14 parameters, and the description fails to compensate by explaining any inputs. Critical required parameters like 'naics_code', 'iso_gl_code', and 'desired_coverages' enums are not mentioned, leaving agents without guidance on what data to provide.

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 ranked carrier recommendations with estimated premium ranges for small commercial risks, using specific verbs and identifying the resource. However, it does not explicitly differentiate from siblings like 'suggest_coverages' or 'classify_business', though the scope is distinct.

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 prerequisites (like needing a classified business first), when to prefer 'connect_with_agent' instead, or what constitutes a valid 'small commercial risk'.

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. It adds valuable behavioral context by specifying results are 'ranked by importance,' but fails to disclose safety profile (read-only vs. destructive), return format structure, or whether suggestions are stored/persisted.

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 single sentence is efficient with no waste, front-loading the core action. However, given the high parameter count (11) and lack of annotations/output schema, the brevity is insufficient rather than admirably concise.

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 with 11 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It omits return value structure, parameter interactions (e.g., how 'serves_alcohol' affects suggestions), and business logic prerequisites.

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?

With 0% schema description coverage across 11 parameters, the description needed to compensate significantly but mentions none of the specific boolean flags (serves_food, has_vehicles, etc.) or codes (naics_code, vertical). It only implies a 'business' context generically, leaving critical parameters like 'handles_customer_data' undocumented.

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 'Suggests which insurance coverages a business likely needs' with specific output formatting 'ranked by importance.' However, it does not explicitly differentiate from siblings like 'explain_coverage' (which explains specific coverages) or 'classify_business' (which likely determines business type).

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 like 'classify_business' (potentially a prerequisite) or 'get_carrier_recommendations.' It lacks prerequisites, exclusions, or conditional logic for when this tool is appropriate.

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