LocalPro — Verified US Local Service Provider Data

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

Since no annotations are provided, the description fully explains behavior: returns vary with/without API key, and contact details are on the listing page. Discloses that full pricing and certifications require a key, and that some data is not returned directly.

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?

Every sentence provides unique information: purpose, authentication behavior, and availability of contact details. Front-loaded with purpose, then details. No fluff.

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 output schema, description covers returned fields at a conceptual level (business description, services, pricing, coverage, link) and distinguishes data tiers. Missing exact field names but sufficient for an agent to understand what to expect.

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 coverage is 100%, so parameters are already documented. Description adds value by noting that niche_id must match the niche used in search_providers, providing necessary cross-tool consistency guidance.

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?

States 'Get a detailed summary of a specific verified service provider.' Clearly specifies verb (get) and resource (summary of provider), and the examples distinguish it from sibling tools like search_providers and list_* tools.

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?

Explains when to use (to get a detailed summary) and provides context on authentication differences and where to find contact details. Does not explicitly state when not to use, but sibling tools are clearly different.

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. It discloses that cities are 'grouped by metro area where applicable' with an example, which adds useful context. However, it doesn't mention behavioral aspects like pagination, rate limits, error handling, or what the output looks like (e.g., list format, fields). For a tool with no annotations, this leaves gaps in understanding how it behaves.

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 well-structured in three sentences. The first states the purpose, the second gives usage guidelines with a sibling tool reference, and the third adds contextual details with an example. Every sentence earns its place, and key information is front-loaded.

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 (2 parameters, no output schema, no annotations), the description is fairly complete. It covers purpose, usage context, and some behavioral details (grouping by metro area). However, without annotations or an output schema, it lacks information on return values, error cases, or performance characteristics, which could be helpful for an agent.

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 schema already documents both parameters thoroughly. The description adds marginal value by mentioning optional filtering by state abbreviation, but doesn't provide additional semantics beyond what's in the schema (e.g., how 'niche_id' relates to 'list_niches', or examples of city slugs). Baseline 3 is appropriate when 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 purpose: 'List available cities and metro areas where verified providers operate for a given niche.' It specifies the verb ('List'), resource ('cities and metro areas'), and scope ('for a given niche'), and distinguishes it from sibling tools like 'search_providers' by explaining its role in discovering valid city slugs before calling that 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 provides explicit guidance on when to use this tool: 'Use this to discover valid city slugs before calling search_providers.' It names the alternative tool ('search_providers') and clarifies the workflow, making it clear this is a prerequisite step for filtering providers by location.

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 present, so the description carries full burden. It states the tool returns niche IDs but lacks details on side effects, authentication, or rate limits. For a safe listing operation, it is minimally adequate.

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 concise sentences that front-load the action and list examples. Every sentence adds value with no 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 simple list tool with no parameters and no output schema, the description covers purpose, usage, and output (niche IDs). Could optionally mention pagination or ordering, but adequate as is.

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?

No parameters exist, and schema coverage is 100%. Per guidelines, zero parameters baseline is 4; the description adds unnecessary detail about categories but no parameter info is needed.

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 'List all available service directories' and provides specific examples of categories, distinguishing it from sibling tools like list_cities and search_providers.

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?

Explicitly positions itself as 'the starting point' for discovering categories, implying when to use. No explicit exclusions or alternatives are mentioned, but the context is clear.

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. It effectively discloses that this is a read-only operation (implied by 'List'), provides context about niche-specific taxonomies with examples, and hints at prerequisite data (niche IDs from list_niches). However, it doesn't mention potential rate limits, error conditions, or response format details, leaving some behavioral aspects uncovered.

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 the core purpose, followed by usage guidance and illustrative examples. Every sentence earns its place by adding critical context without redundancy, making it efficient and well-structured for an AI agent.

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 (1 parameter, no output schema, no annotations), the description is largely complete. It covers purpose, usage, and behavioral context adequately. However, the lack of output schema means the description doesn't explain return values (e.g., list format, pagination), which is a minor gap in completeness for a tool that outputs data.

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 schema already fully documents the niche_id parameter. The description adds minimal value beyond the schema by reinforcing the need for valid niche IDs and giving examples ('coated-local', 'radon-local'), but doesn't provide additional syntax or format details. Baseline 3 is appropriate when 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 specific action ('List the valid service type categories') and resource ('for a given niche directory'), distinguishing it from siblings like list_niches or search_providers. It provides concrete examples (e.g., 'coated-local' has epoxy, polyaspartic) to illustrate the purpose beyond just the tool name.

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?

Explicitly states when to use this tool ('Use this before calling search_providers with a service_type filter to ensure you pass a valid value') and names a specific alternative (search_providers). It also implies context by noting each niche has its own taxonomy, guiding usage relative to other tools like list_niches.

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 provided, so description carries the burden. It discloses return fields, Google Maps URL availability, and coverage. However, it does not mention pagination, rate limits, or behavior when no results found.

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 paragraph that covers purpose, return values, and prerequisites efficiently. It is front-loaded with the core functionality, but could be slightly more structured for readability.

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 complexity (9 categories, 4 parameters, no output schema), the description adequately covers what is returned, coverage area, and how to use parameters. Could mention handling of no results or edge cases.

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 baseline is 3. The description adds value by referencing prerequisite calls for valid parameter values, but does not significantly enrich parameter meaning beyond 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 clearly states the tool's purpose: searching for verified local service providers across 9 specific trade categories. It lists what is returned (name, rating, etc.) and distinguishes from sibling tools like get_provider.

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?

Explicitly instructs to use list_niches and list_service_types first to get valid IDs, and mentions list_cities for city slug. This provides clear when-to-use guidance and prerequisites.

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