Booqer

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

Goes well beyond the read-only annotations: booked and blocked times are excluded from results, times are returned as ISO-8601 with offset, the shop timezone is America/New_York, and the endpoint is rate limited per IP and per shop. These are exactly the operational traits an agent needs before calling.

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 trigger condition is front-loaded and most sentences carry distinct facts (exclusions, timezone, non-reservation, rate limits). A few sentences restate format details already present in the schema, which is mild redundancy rather than 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?

With an output schema present, return values need no explanation, and the description still covers trigger, exclusions, timezone, dependency on get_business/search_businesses, non-reservation, and rate limits. Nothing needed to invoke it correctly 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?

Schema coverage is already 100%, so the baseline is 3; the description adds the semantic role of offering ('selects that shop's rules from get_business') and reiterates the date/start formats and timezone. Most format detail duplicates the schema, but the offering behavior is genuinely new information.

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 ('check availability ... Lists the open 30-minute slots for one shop and one date') and constrains scope to a single shop/date, which clearly separates it from get_booking_status and request_booking. An agent can identify what it returns without opening the 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?

'Use this when the user wants to check availability ... before booking' gives clear trigger context, and 'Does not reserve a slot' rules it out as a write path. It does not, however, explicitly name request_booking as the follow-up tool, so the alternative is implied rather than stated.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description's remaining contribution is the set of possible status values, which is largely redundant because an output schema exists, plus the useful constraint that no customer identifiers are needed. It adds some invocation context but nothing deep about 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?

Three brief sentences with the usage trigger front-loaded and zero filler. The enumeration of status values is the one element that could be trimmed given the output schema, keeping it out of the top tier.

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, single-parameter lookup with a full output schema and complete annotations, the description covers the trigger, input scope, and result vocabulary. It omits only edge behavior such as unknown or expired request ids, a minor gap for this 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?

Schema description coverage is 100% and the single request_id parameter is fully documented in the schema (UUID type, example value, and its origin in request_booking). The description adds only the negative note that name/phone/email are not inputs, so the baseline 3 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?

The description states a specific verb and resource (check the status of an appointment) and scopes the resource to local home-service bookings, which separates it from request_booking, check_availability, and request_service. It is clear without naming a sibling explicitly, so it lands just below the top tier.

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?

"Use this when the user wants to check the status of a local home-service appointment" gives an explicit trigger condition, and "No customer name, phone, or email" usefully tells the agent not to solicit extra identifiers. There is no explicit when-not or named alternative, so it stops short of a 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?

Annotations already declare readOnlyHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing conditional field presence — phone 'when published' and booking_rules/emergency_phone 'when that shop has them' — which tells the agent output shape can vary.

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?

Usage guidance is front-loaded ahead of the return description, and both sentences carry weight. Enumerating the return fields is somewhat redundant given an output schema exists, but it remains compact and readable.

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 single-parameter read tool with an output schema and full annotation coverage, this is complete: the agent knows when to call it, what id to pass, and what shape of data varies conditionally. Nothing needed to invoke it correctly 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?

Schema description coverage is 100% and shop_id is already documented with examples, so baseline is 3. The description reinforces the provenance of the id (from search_businesses) but adds no syntax or format detail the schema lacks.

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 (read) and resource (one enrolled home-service business), and explicitly contrasts it with search_businesses and resolve_business, so an agent can distinguish it from siblings without opening the 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?

Gives an explicit precondition: use when the user wants one business AND search_businesses or resolve_business already returned its id. This names the alternative tools and the condition that selects this one rather than them.

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?

Goes well beyond the annotations: it warns that a repeat call can create a duplicate booking, explains idempotency_key behavior, requires consent text be shown first, lists rejected email domains, states per-IP/per-shop rate limits and a daily cap, and defines the 2-hour/21-day start window. This is exactly the mutation-risk context an agent needs on top of destructiveHint=true.

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?

Dense single block, but front-loaded with the trigger condition and duplicate-booking warning, and every clause carries a rule the agent must apply. Some sentences duplicate the schema verbatim (ISO-8601 example, disposable-domain rejection), which is minor redundancy rather than padding.

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 12-parameter mutation tool with 7 required fields, it covers consent, validation, timing windows, deduplication, rate limits, and return values; with an output schema and destructive annotation present, nothing an agent needs to call this correctly 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?

Schema description coverage is 100%, so the baseline is 3, but the description adds cross-field semantics the schema does not: job_summary falling back to problem, service_area inference, address requirements per consult type, and offering/start provenance. It does repeat some schema content (start format, email rejection), which keeps it from a 5.

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 ('book a local home-service appointment', 'Confirms a free consult when the slot is open'), which cleanly separates the consult flow from the general service flows. Sibling differentiation is partial: it explicitly references get_booking_status and get_business as supporting tools but never says when to prefer request_service or submit_service_request instead of this one.

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 a clear precondition ('has already chosen an open time') and an explicit alternative ('if unsure, check get_booking_status first'), both of which direct agent behavior. It stops short of naming the competing booking siblings as alternatives for non-consult cases, so routing is clear but not exhaustive.

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 readOnly/idempotent annotations, it discloses important behavior: the call does not store a request, does not confirm a booking, and is rate-limited. It also names the widget URI, adding useful 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 compact and front-loads the usage condition, followed by behavior, parameter mapping, widget URI, and constraints. Each sentence contributes useful information without unnecessary repetition.

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 annotations, complete input schema, and output schema, the description provides enough context for correct selection and invocation. It covers the key non-obvious behavior: no persistence, no booking confirmation, and rate limiting.

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 both parameters are already well documented in the schema. The description adds source terminology for business_id and repeats the shop_id fallback rule, but it does not materially expand parameter semantics beyond the structured fields.

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 and resource: opening a quote form/widget for one enrolled home-service business. It explicitly distinguishes this from booking a confirmed appointment time, so an agent can separate it from request_booking.

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 a clear trigger condition: use when the user wants to open a quote form rather than book a confirmed appointment. It also explains business_id versus shop_id fallback behavior, which helps invocation.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds non-obvious behavior beyond that: ambiguous matches are refused, exactly one identity is returned, and phone/email/street address are deliberately withheld. That refusal and output-scoping detail is genuinely useful and not derivable from the annotations.

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?

Three short sentences, zero filler, with the primary usage condition front-loaded and the behavioral caveats (refusal, withheld fields) trailing. Every sentence carries distinct information.

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?

An output schema exists, so the description is not obliged to explain the return shape, and it correctly spends its words on the refusal rule and the fields deliberately excluded from the response. Coverage is solid for a 3-optional-parameter resolver; the only gap is the absence of routing guidance to sibling lookup tools.

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%, with each of the three parameters already carrying an example and the 'place' parameter documenting its own ambiguity refusal. The description restates the input modes but adds no syntax or format detail beyond the schema, so the baseline 3 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?

The description states a specific verb and resource ('resolve one enrolled local home-service business') and enumerates the three input modes (domain, place, phone). It distinguishes the tool as a single-entity resolver rather than a search, but never names the sibling tools (search_businesses, get_business) it contrasts with, so the differentiation is implied rather than explicit.

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 a clear triggering condition ('when the user wants to resolve one... business') and the qualifying inputs, so an agent knows the context in which to reach for it. There are no exclusions or explicit alternative routes (e.g., use search_businesses when the match is ambiguous or when several businesses are wanted), which keeps it short of a 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?

Goes well beyond the readOnly/openWorld annotations by disclosing directory coverage limits (Florida pole barn and gate/security), the exact return fields, and several edge behaviors: non-enrolled trades return no businesses with an explanatory message, out-of-service-area cities are excluded, and booqer-demo-shop is suppressed unless matched by exact name or id.

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?

Front-loads the usage trigger, then coverage, then return shape, then caveats in a logical sequence with no filler. It is on the long side, but nearly every clause carries distinct information an agent needs; minor tightening of the return/suppression sentences is possible.

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?

An output schema already exists, so return values are partly redundant, yet the description still gives the agent the coverage boundaries, failure semantics, and the demo-shop suppression rule that no structured field expresses. Nothing needed to call it correctly 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?

With one parameter at 100% schema coverage the baseline is 3, but the description adds real semantics: the query matches across name, category, service, location, or phone. That tells the agent what kinds of strings are valid beyond the schema's three examples.

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 precise verb (searches) and resource (Booqer directory of enrolled home-service businesses) and enumerates the trade categories it covers. It is clearly distinguishable from siblings like get_business, resolve_business, and check_availability because it describes directory lookup by name/category/service/location/phone.

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?

Opens with an explicit trigger ('Use this when the user wants to find a local home-service business or appointment'), which is clear context for invocation. It does not name a sibling alternative or state when to prefer get_business over search, but the coverage constraints implicitly scope usage.

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=false, destructiveHint=true, openWorldHint=true and idempotentHint=false, so the safety profile is covered. The description adds that the payload is forwarded to a third-party business and is form-scoped, but it does not explain the destructive/non-idempotent consequences (e.g., duplicate submissions, whether a request can be withdrawn).

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 short sentences with the action and target front-loaded; the scoping sentence carries real information. No filler or restated boilerplate, though it stops just short of maximal density.

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?

An output schema exists, so return values need no explanation, and the schema fully documents the 8 parameters. What remains missing is the consequence of a destructive, non-idempotent write to an external business and the relationship to the request_* siblings, which is thin for an 8-parameter mutation tool.

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 every parameter including the consent gate, ISO-8601 start format and optional phone/service_address rules is already documented in the schema. The description merely restates a subset of those fields, adding no format or constraint detail beyond the structured data.

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 verb and resource: it 'sends the user's quote request ... to the chosen business', and it enumerates the payload fields. It is clear on its own, but it never distinguishes itself from closely named siblings like request_service or request_booking, leaving overlap unresolved.

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?

'Called by the quote form only' is a real usage constraint that tells the agent this is not a general-purpose submission tool, which is more than nothing. However, it names no alternatives and gives no condition for choosing request_service or request_booking instead, so the routing guidance is only implied.

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