Waves Pest Control & Lawn Care

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

With no annotations, the description carries the full behavioral burden. It usefully discloses provenance and freshness ('engine-derived, refreshed from live pricing configuration') and the public URL mirror, but it does not explicitly state read-only behavior, authentication needs, rate limits, or whether any filtering/side effects exist. For a simple no-param read tool this is adequate but not rich.

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 compact sentences front-load the resource and return shape, then immediately route exact-quote needs to the sibling tool. The URL is included only as a useful equivalence reference; there is no waste.

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?

There is no output schema and no annotations, so the description must carry the burden. It explains the return shape at a high level (low/high per service), provenance, freshness, and the exact-quote limitation. Minor gaps remain around currency and whether the full service list is included, but it is sufficient for correct 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?

The tool has zero parameters, so the baseline is 4. The description adds no parameter meaning because none exist, which is appropriate rather than missing.

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 resource returned: published price ranges with low/high values per service, including provenance as engine-derived and refreshed from live pricing configuration. It distinguishes itself from exact quoting by pointing to how_to_request_quote, though it lacks a direct verb such as 'get' or 'retrieve'.

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?

It gives clear usage context by stating that exact per-property quotes require customer contact details and directing the agent to how_to_request_quote. It does not explicitly say 'use this tool when you need published ranges,' but the implication is strong and there are no misleading exclusions.

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 exist, so the description bears the full burden. 'Fetch' and 'customer-visible' do disclose the operation is a read and that results are scoped to customer-visible services, which is real behavioral context. It does not say what happens when a key is missing/invalid or whether auth/tenant scope applies.

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?

A single sentence with the resource and the key parameter front-loaded, and the return-field list in parentheses. No 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?

For a simple one-parameter read, the description covers purpose and return shape, which substitutes for the absent output schema. It still leaves gaps on key provenance/format, error behavior, and its relationship to list_services.

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 0%, so the single service_key parameter has no structured documentation. The description only restates that the key identifies the service; it gives no format or source hint (where the key comes from). It does compensate somewhat by listing the response fields, which is useful since there is no output 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?

States a specific verb ('Fetch') and resource ('one customer-visible catalog service') keyed by service_key, and enumerates the fields it returns. The singular 'one' distinguishes it from list_services without naming that sibling explicitly.

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 requirement to supply a service_key implies this is the lookup path once a key is known, and 'one' implies complementarity with a listing tool. However, it never names list_services as the way to discover keys, nor states when not to use it (e.g., bulk retrieval).

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 disclosure burden. "List" implies a read-only operation and the phrase "cities and counties Waves Pest Control serves" tells the agent roughly what comes back, but nothing is said about the result being a static/fixed dataset, whether it is paginated or exhaustive, or the format returned. For a zero-argument lookup the behavioral surface is small, so this is adequate but not rich.

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?

One short sentence that front-loads the action and the dataset boundary. Every word earns its place with zero boilerplate or repetition of the tool name.

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?

With no annotations, no output schema, and zero parameters, the description supplies the essential information: this returns a coverage list of cities and counties. A brief note on whether the list is exhaustive or how it is returned would close the remaining gap, but nothing critical is missing for an agent to call it correctly.

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, so there is nothing for the description to disambiguate; baseline for a no-param tool is 4. The absence of parameters is not explicitly acknowledged, but the schema makes it evident.

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 a specific verb ("List") and a precisely scoped resource (Southwest Florida cities and counties served by Waves Pest Control). It is trivially distinguishable from siblings like list_services and get_pricing_ranges, which cover services and pricing rather than geography, so an agent can route to it without opening any schema.

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 explicit when-to-use, when-not-to-use, or named alternative is given. However, the tool's scope is so narrow and unambiguous (any question about coverage area) that correct usage is strongly implied rather than inferred from nothing. It stops short of the routing language that would earn a 4 or 5.

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, so the description carries the burden; it does disclose that the documented endpoint has side effects and a defined response shape, which is useful. However, it doesn't state that calling this tool itself is a read-only documentation lookup, nor anything about auth or rate limits.

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?

A single dense sentence that front-loads the purpose before the content list and alternatives. Slightly packed with parentheticals, but nothing is redundant.

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?

With no output schema, the description does the right thing by listing what the returned reference contains (contact fields, service keys, response shape, side effects). Only the read-only nature of the tool call itself is left implicit.

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, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly frames the output as a reference document rather than implying any input.

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 a concrete resource (the public quote endpoint's HTTP contract) and enumerates its contents: required contact fields, service keys, response shape, side effects. It doesn't explicitly contrast itself with get_pricing_ranges or list_services, so an agent must infer that this is the 'exact quote' path versus rough pricing.

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 word 'EXACT' and the mention of 'human-facing alternatives (quote page, online booking, phone)' imply when this reference applies, but there is no explicit when-to-use rule or named sibling alternative such as 'for ballpark figures use get_pricing_ranges'.

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 behavioral burden and does disclose the scope filter ('customer-visible') and the exact fields returned, plus what is deliberately excluded (descriptions on the website, prices via another tool). It omits whether results are paginated or ordered, but for a zero-parameter read-only catalog the disclosed shape is substantial.

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?

One front-loaded sentence that names the resource and its contents before adding the pricing cross-reference. The parenthetical category list and website URL are dense but each earns its place by telling the agent what is and is not included.

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?

With no annotations, no output schema, and no parameters, the description is nearly complete: it states the scope, the returned fields, and where to get the two things it does not return. A note that it is read-only and that results are unpaginated would close the remaining gap.

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 no parameters, so there is no parameter semantics to explain and the baseline of 4 applies.

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 a specific verb and resource ('List the customer-visible Waves Pest Control service catalog') and enumerates the categories and fields returned, so an agent knows exactly what it gets. It clearly distinguishes itself from get_pricing_ranges but never names get_service, leaving the boundary with that sibling slightly ambiguous.

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?

Gives clear usage context (catalog names, categories, billing type, visit frequency) and explicitly routes pricing requests to get_pricing_ranges. It stops short of saying when not to use it or directing agents to get_service for individual descriptions, so the routing is helpful but incomplete.

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