LocalPro — Verified US Local Service Provider Data

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 thoroughly discloses auth-dependent behavior (with vs. without API key), lists exactly which fields are returned in each case, and clarifies that contact details are only available via listing_url. This goes well beyond the minimum and leaves little guesswork.

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 three sentences long, front-loaded with the main purpose, then detailing return fields and auth variations. Every sentence carries essential information with no filler or redundant phrasing. This is an exemplary model of conciseness.

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 there is no output schema, the description must explain return values itself. It does so comprehensively, covering business description, services, pricing details, coverage area, service details, listing link, and the auth-dependent extra fields. It also explains where to find contact details. This is fully complete for the tool's complexity.

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 100% coverage with example values for niche_id and provider_slug. The description adds no extra parameter-level meaning beyond what the schema states. Thus, the baseline of 3 is appropriate since the schema fully documents the parameters.

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: 'Get a detailed summary of a specific verified service provider.' The verb 'Get' and resource are precise, and it distinctly differentiates from sibling tools like search_providers by emphasizing 'specific' vs. searching. It also enumerates what is returned, removing ambiguity.

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 does not explicitly state when to use this tool vs. alternatives, nor does it mention exclusions. It implies a prerequisite by referencing 'specific verified service provider,' but the direct guidance to use search_providers first comes only from the input schema, not the description itself. This is implied usage, not explicit.

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, the description carries the transparency burden. It discloses meaningful grouping behavior ('Cities are grouped by metro area') and gives a concrete example of metro coverage (Minneapolis/St. Paul suburbs). It doesn't mention return format, pagination, or error behavior, but for a simple listing tool, this is reasonably transparent.

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 three sentences, all of which serve a purpose: stating the function, giving usage guidance, and explaining a key behavioral detail. It is front-loaded with the verb and resource, and there is no redundant filler.

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 tool is simple with two parameters, one required, and full schema coverage. The description covers purpose, when to use it, and grouping behavior. It doesn't describe the return value structure, but the lack of an output schema is somewhat mitigated by the clarity of the listing behavior. Slightly more detail on what the output looks like would push it to 5.

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%, with parameter descriptions already explaining 'niche_id' and 'state.' The description adds context about metro-area grouping and the 'minneapolis-mn' slug format, but this is more about output behavior than parameter semantics. It repeats the optionality of state already implied by the schema, so it doesn't significantly elevate beyond the baseline.

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 a specific action ('List') and a specific resource ('available cities and metro areas where verified providers operate'), scoped by 'for a given niche.' It distinguishes itself from sibling tools like list_niches and search_providers by specifying its role in discovering city slugs.

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 explicitly says 'Use this to discover valid city slugs before calling search_providers,' providing clear when-to-use guidance and naming the downstream tool. It also notes the optional state filter, which helps the agent decide how to invoke it.

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, the description carries the burden of transparency. It clearly indicates a read-only listing operation ('List all available'), enumerates the category domains, and discloses that the return value is niche IDs. It does not discuss pagination or auth, but for a zero-parameter list tool this is 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?

The description is three sentences, front-loaded with the primary action and scope. The list of example categories is useful context, and there is no redundant or filler content.

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 zero-parameter tool with no output schema, the description sufficiently covers purpose, what it returns, and how it fits into the broader workflow ('needed for all other tools'). No significant gaps remain.

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 takes zero parameters, with a schema coverage of 100% (empty properties). The description adds value by explaining what the output represents (niche IDs needed for other tools), which satisfies the baseline for parameter-less tools.

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 ('List') and names a clear resource ('all available service directories in the LocalPro network'). It also explains that the result is categories of verified providers and references the needed niche IDs, distinguishing it from sibling tools like list_cities or 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?

The description explicitly frames the tool as the 'starting point' and states that it returns 'niche IDs needed for all other tools', giving clear guidance on when to use it. It does not explicitly list alternatives or when not to use it, but the priority context is strong.

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 burden. It discloses niche-specific taxonomy and gives examples, but does not explicitly state return type, error behavior, or confirm read-only nature. The 'list' verb implies read-only but lacks deeper behavioral 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?

Two sentences: first states purpose, second gives usage guidance and examples. Front-loaded, no fluff, every sentence earns 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?

For a simple list tool with one parameter and no output schema, the description sufficiently explains what it does and when to use it. It lacks explicit mention of response format, but examples and naming imply a list of valid values, making it mostly complete.

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% with niche_id well-documented in the schema (including examples and reference to list_niches). The description adds context about niche-specific taxonomy but does not materially extend the parameter semantics beyond what the schema already provides.

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 (list) and resource (valid service type categories for a given niche directory). It distinguishes from sibling tools like list_niches and search_providers by focusing on the niche-specific taxonomy of service types, with concrete examples.

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 tells when to use this tool: 'Use this before calling search_providers with a service_type filter to ensure you pass a valid value.' This provides clear context and a direct reference to an alternative workflow, fulfilling the dimension fully.

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 output fields (name, rating, review count, certifications, etc.) and includes a caveat ('Google Maps URL when available'). However, it does not mention authentication requirements, rate limits, or what happens when no results are found, leaving a modest gap.

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 dense but well-organized: purpose, return fields, coverage, and prerequisite calls are presented in logical sequence. The long list of categories is necessary context for a niche-specific search tool, so it earns 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?

For a search tool with no output schema, the description is nearly complete: it details the return payload, coverage limitations, and prerequisite sibling tools. It lacks explicit error/empty-result behavior, but that is non-critical for a read-only search operation.

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 the baseline is 3. The description adds value by pointing to list_niches and list_service_types for valid parameter values, and by explaining that city and service_type act as filters. This enriches the schema 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 opens with a specific verb and resource ('Search for verified local service providers') and enumerates 10 trade categories, making the tool's scope unmistakable. It also lists all return fields, clearly distinguishing it from sibling tools like get_provider (single provider) and list_niches/list_service_types (metadata lookups).

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 explicitly instructs agents to 'Use list_niches first to get valid niche IDs, and list_service_types for valid service_type values,' providing direct cross-tool usage guidance. It also notes geographic coverage ('major US metro areas'), setting expectations for when the tool is appropriate.

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