valet-parking-directory

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds behavioral details beyond annotations: the 100-mile cap, the nearest-first ordering, and the empty-array behavior when no operators are within range. This is useful context, though it does not cover all potential edge cases 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 two sentences, front-loaded with the primary action, and every word adds value. It avoids redundancy with the schema and annotations.

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 (4 params, output schema present, strong annotations), the description covers purpose, usage scenario, and key edge behavior (empty array). The 100-mile cap and service filtering are highlighted, making it complete enough for an agent to select and invoke 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?

Schema description coverage is 100%, so baseline is 3. The description adds semantic value by explaining the 'service' parameter as 'narrowing' results and referencing 'coordinate' for lat/lng. It does not detail 'limit', but the schema already documents it fully.

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: 'List nearest valet operators within a 100-mile cap of a coordinate, optionally narrowed by service.' It uses a specific verb ('List') and resource ('nearest valet operators'), and uniquely mentions the 100-mile cap and ranking nearest-first, distinguishing it from siblings like valet_find_operators_in_city.

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?

Explicit usage guidance is provided: 'Use this when a user is in a city with no listed operators and you need the closest available fallback ranked nearest-first.' This clarifies when to invoke the tool and implies when not to (when operators are listed in the city), serving as an effective alternative to siblings.

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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds valuable behavioral details: the ranking order (premium tier first, then name) and the empty-array return when no operators are listed, which go beyond structured fields.

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, front-loaded with the primary action, and every clause adds value. No redundant restatement of the title or schema, making it appropriately concise and structured.

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 filtered list tool with good annotations and an output schema, the description covers purpose, usage context, ordering, and empty-return behavior. It doesn't explicitly mention sibling alternatives, but the provided usage guidance is sufficient for selection.

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 fully documents all four parameters. The description does not add parameter-level detail beyond what the schema already states, so the baseline of 3 is appropriate.

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?

Description states a specific verb ('List') plus resource ('valet operators') and scope ('serving a city slug plus state slug, optionally narrowed by service'). It clearly distinguishes from siblings by noting the city is already disambiguated and mentions the ranking (premium tier first then 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?

Provides explicit context for use: 'when an agent has a city already disambiguated and wants its operator roster ranked premium tier first then name.' This implies when to use it relative to sibling tools, though it does not explicitly name alternatives or 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?

The description adds useful behavioral context beyond the read-only/idempotent annotations: it discloses the ranking order (premium tier first, then distance) and the empty-array return when no matches exist. This is meaningful for the agent's expectations.

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, front-loaded with the main action, and no wasted words. It includes essential information without redundancy or bloat.

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 full schema and annotations, the description covers the key behavioral aspects (ranking, empty results, radius context). It is sufficient for an agent to invoke the tool correctly without needing additional explanation.

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 repeats the radius_miles requirement and contextual radius guidance already present in the schema, but adds no new parameter semantics beyond that. It does not explain limit or service parameters, though the schema fully covers those.

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 finds valet operators within a radius of a coordinate, specifies ranking (premium tier first, then distance), and is differentiated from sibling tools like valet_find_nearest_operators or valet_find_operators_in_city via the radius-based scope.

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 explicitly states when to use the tool: when you have a coordinate and an event-context radius, with concrete examples (5mi, 25mi, 50mi). It does not explicitly name alternatives or provide when-not guidance, but the context is clear enough for basic 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?

The description adds behavior beyond annotations by noting 'Returns isError on slug 404 or upstream outage,' which communicates error semantics. The readOnly, idempotent annotations already cover safety, and this description enriches understanding without contradiction.

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 two sentences, front-loaded with the action and resource, and each sentence earns its place: one for scope/fields, one for usage context and error behavior. No redundancy or 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?

For a simple single-parameter get-by-slug tool with robust annotations and an output schema, the description covers all necessary context: what the tool does, when to use it, and key error behavior. Nothing essential is missing.

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 already provides a detailed description of the slug parameter (kebab-case, lowercase, digits, hyphens) with 100% coverage. The tool description merely references 'by slug' without adding further parameter semantics, so the baseline of 3 is appropriate.

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 gets the full operator profile by slug and enumerates the specific fields included (address, phone, website, services, venues_served, FAQs, tipping note). It distinguishes itself from sibling search tools by focusing on a direct slug-based lookup.

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 gives explicit when-to-use guidance: 'Use this when an agent has a slug from a search tool or directory URL and needs the complete profile to rank or present.' It does not explicitly name alternative tools or when not to use, but the context implies searching tools handle discovery.

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?

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint=false, covering safety. The description adds valuable context beyond annotations: 'Returns the in-bundle catalog; no upstream call; no isError path.' This informs the agent about the tool's execution model and error behavior, although it isn't a full behavioral contract.

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, front-loaded with the core purpose, followed by usage guidance and behavioral notes. Every sentence earns its place; no fluff or repetition. The structure is ideal for quick comprehension.

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 zero-parameter, read-only list tool with an output schema, the description fully covers purpose, use case, and execution traits. The presence of an output schema eliminates the need to describe return fields, and the description confirms the tool is safe and self-contained. It is complete for the tool's simplicity.

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 description cannot add parameter-level meaning. Per guidelines, a no-parameter tool receives a baseline of 4. The description's mention of '9 canonical service slugs' is an output detail rather than a parameter semantic, but it gives a sense of the result size.

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 verb and resource: 'List the 9 canonical valet service slugs with display name and category.' It distinguishes itself from sibling tools by focusing on the service taxonomy, while siblings handle operators and cities. The 9-slug detail is concrete and unambiguous.

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: 'Use this when an agent needs to validate or discover the supported service taxonomy before composing a follow-up search.' It even names a sibling tool as a companion, showing awareness of alternatives. Clarifies that no upstream call occurs, which sets expectations for reliability and speed.

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?

Beyond the annotations (readOnlyHint, idempotentHint), the description adds valuable behavioral context: results are 'tier-then-name ranked' and 'Invalid service slugs surface the 9 canonical alternatives.' These details help the agent understand ordering and error handling.

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 core purpose, followed by usage and a notable behavior. Every sentence contributes meaning without unnecessary 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?

With an output schema present, the description appropriately focuses on inputs, usage, and behavior rather than return values. It covers key aspects like cross-state matching, ranking, and invalid slug handling. A minor gap is not mentioning the limit parameter or pagination, but these are already defined in the schema.

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 descriptions for all three parameters, so the description does not need to elaborate much. It mentions the two required slugs but adds no additional meaning beyond schema details like the enum for service_slug and the example city_slug.

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: 'Search valet operators by service slug plus city slug across all matching states.' It specifies the exact inputs and scope, and distinguishes itself from siblings by noting the cross-state, tier-then-name ranked list output.

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 an explicit usage condition: 'Use this when an agent has both a service slug and a city slug and wants a cross-state tier-then-name ranked list.' This gives clear context for when to invoke the tool, though it does not explicitly name alternative tools or describe when not to use 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral details beyond annotations, including 'population-ranked results' and 'Empty array if no matches.' It also previews the return meaning. With output schema present, this is solid additional 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 two sentences, front-loaded with the primary function, and then provides usage context and a key behavioral note (empty array). Every sentence earns its place with 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 read-only search tool with 2 parameters, an output schema, and strong annotations, the description fully covers the tool's purpose, when to use it, and essential edge behavior (no matches). It also immediately connects to related tools, making the description complete for an agent selecting and invoking it.

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 parameters (query and limit) already have detailed descriptions covering prefix semantics, min length, default, and max. The tool description adds context about population ranking and the canonical output fields, but it doesn't add new parameter-level syntax or meaning beyond the schema, so the baseline of 3 is appropriate.

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 states a specific action ('Search the cities directory by name prefix'), a resource (cities directory), and a distinguishing trait (population-ranked results). It also clarifies the output (canonical city slug, state slug, lat/lng), which clearly differentiates it from sibling tools that find operators.

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 when to use this tool: 'when an agent needs to resolve a partial city name into a canonical city slug plus state slug plus lat/lng before composing valet_find_operators_in_city or valet_find_operators_near.' This names alternatives and provides an explicit context, going beyond mere implication.

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