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

With no annotations provided, the description carries the full burden. It clearly indicates this is a read operation ('Get') and specifies what data is returned, including differences for premium businesses. However, it lacks details on error handling, rate limits, authentication needs, or response format.

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 efficiently structured in two sentences: the first states the core purpose and data returned, the second adds valuable context about premium features. Every word contributes meaning without 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?

For a read-only tool with no annotations and no output schema, the description does well by specifying the scope of returned data and premium distinctions. However, it could be more complete by mentioning response structure or error cases, though the high schema coverage helps compensate.

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 the input schema already fully documents the two parameters (slug and business_id). The description adds no additional parameter semantics beyond what the schema provides, maintaining the baseline score.

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 ('Get') and resource ('HeySpark-listed business') with specific details about what information is retrieved (address, hours, services, reviews summary, contact information, plus photos and special offers for premium businesses). It distinguishes from sibling tools like 'get_reviews_summary' by covering broader business details.

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 implies usage for retrieving comprehensive business information, but provides no explicit guidance on when to use this tool versus alternatives like 'search_businesses' or 'get_reviews_summary'. No prerequisites or exclusions are mentioned.

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 must fully disclose behavioral traits. It mentions that 'review highlights' are 'Premium tier only,' which adds useful context about access restrictions. However, it lacks details on rate limits, authentication needs, error handling, or the format of the summary (e.g., JSON structure). For a tool with no annotations, this leaves significant gaps in understanding its 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 concise and front-loaded, stating the core purpose in the first clause. It efficiently includes additional details about the summary content and tier restrictions in a single sentence. There's no unnecessary verbosity, and every part contributes value, though it could be slightly more structured for clarity.

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 moderate complexity (1 parameter, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the purpose and tier restrictions but lacks details on output format, error cases, or integration with siblings. Without an output schema, it should ideally explain what the summary returns, but it only hints at 'overall rating, review count, and review highlights.' This makes it adequate but not fully comprehensive.

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, with the 'business_id' parameter fully documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, such as format examples or validation rules. According to the rules, with high schema coverage, the baseline is 3, as the schema handles 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 purpose: 'Get a reviews summary for a HeySpark-listed business.' It specifies the verb ('Get'), resource ('reviews summary'), and target ('HeySpark-listed business'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'get_business_details' or 'search_businesses', which might also provide review-related information, so it falls short of a perfect 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 minimal usage guidance. It implies the tool is for businesses listed on HeySpark, but it doesn't specify when to use this tool versus alternatives like 'get_business_details' (which might include reviews) or 'search_businesses' (which could filter by ratings). There's no mention of prerequisites, such as needing a Premium tier for highlights, or exclusions for non-listed businesses.

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 discloses the tool's read-only nature (listing data) and output format (categories with counts), but lacks details on behavioral traits like rate limits, authentication needs, pagination, or data freshness. It doesn't contradict annotations (none exist), but offers only basic operational context.

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, well-structured sentence that front-loads the core action ('List all available business categories') and adds essential detail ('on HeySpark with the number of active businesses in each'). Every word earns its place with zero waste, making it highly efficient 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?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally complete. It explains what the tool does but lacks context on output format details (e.g., structure of returned categories), error handling, or integration with siblings. For a simple list tool, this is adequate but leaves gaps in full agent guidance.

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 0 parameters, and schema description coverage is 100% (empty schema is fully described). The description adds no parameter semantics (none needed), so a baseline of 4 is appropriate as it compensates adequately for the lack of parameters by clearly stating the tool's purpose without redundancy.

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 ('List') and resource ('business categories on HeySpark'), specifying what data is returned ('with the number of active businesses in each'). It distinguishes from siblings like 'get_business_details' (specific business) and 'search_businesses' (filtered search), though not explicitly named. A 5 would require explicit sibling differentiation.

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 description's scope ('all available business categories'), suggesting this is for broad overviews rather than specific queries. However, it lacks explicit guidance on when to use this versus alternatives like 'search_businesses' for filtered results or 'get_reviews_summary' for review data. No misleading information is present.

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 discloses key behavioral traits: the tool returns a list with specific fields, premium businesses are prioritized, and it supports filtering by multiple criteria. However, it lacks details on rate limits, authentication needs, error handling, or pagination behavior beyond the offset parameter, leaving some gaps 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 front-loaded and efficient: two sentences cover purpose, filters, output, and result prioritization with zero waste. Every phrase adds value, making it appropriately sized and well-structured for quick 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?

Given the complexity (9 parameters, no output schema, no annotations), the description is mostly complete: it explains what the tool does, key filters, output format, and result ordering. However, it lacks details on error cases, authentication, or exact return structure, which could be helpful for a search tool with many parameters. It's adequate but has minor 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 schema description coverage is 100%, so the schema fully documents all 9 parameters. The description adds marginal value by summarizing filter types (keyword, category, city/state, coordinates) and implying radius_miles requires latitude/longitude, but doesn't provide additional syntax or format details beyond the schema. This meets the baseline of 3 when 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 purpose: 'Search for local businesses listed on HeySpark' with specific filters (keyword, category, city/state, coordinates) and output details (name, category, location, rating, contact info). It distinguishes from siblings like get_business_details (specific business) and list_categories (categories only) by emphasizing search functionality across multiple criteria.

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 clear context for when to use this tool: for searching businesses with various filters. It implies alternatives by mentioning 'Premium-tier businesses appear first,' suggesting prioritization in results. However, it doesn't explicitly state when not to use it or name specific sibling tools as alternatives, keeping it at a 4.

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