Find real businesses and book appointments. Books via Cal.com; imports 12 platforms.
Scored across 9 tools
Each tool targets a distinct operation: pre-flight URL checking, business discovery, directory lookup, cost preview, scheduling, status polling, outcome retrieval, and health probing. Even similar pairs like check_booking_link/import_booking_url and get_status/get_outcome are clearly differentiated by their descriptions and lifecycle stages.
Tool names follow a consistent verb_noun pattern (check_, find_, get_, import_, preview_, schedule_, verify_) with snake_case. The only minor deviation is self_test, which reads as a noun rather than an imperative but is still clear and matches the overall style.
With 9 tools, the server is well-scoped for an appointment booking workflow: discovery, verification, import, pre-flight check, cost estimation, scheduling, and async operation tracking. Each tool has a clear role and none feel redundant or extraneous.
The tool surface covers the full appointment lifecycle — find and verify businesses, import booking URLs, check compatibility, estimate cost, schedule with hold/confirm/reschedule/cancel, and retrieve outcomes for async operations. No obvious dead ends or missing core operations for the stated purpose.
Free, instant pre-flight check for a booking URL. Classifies which booking platform a URL belongs to and tells you whether import_booking_url will accept it, WITHOUT fetching the page or spending money. Returns the platform, the exact smb_id import_booking_url would assign, the channels the booking will route through, and the inferred country. Use it to de-risk a paid booking BEFORE calling import_booking_url + schedule_appointment. [free, no key]
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full http(s) URL to classify, e.g. 'https://cal.com/jane' or… |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds meaningful behavioral context beyond that: it performs no network fetch, incurs no cost, requires no key, and returns a specific set of derived values including the exact smb_id. This tells the agent exactly what side effects to expect (none) and what output to anticipate.
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 every sentence adds value: what it does, what it avoids, what it returns, and when to use it. Key behavioral constraints are front-loaded, and the '[free, no key]' tag is a compact useful addition.
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 a single parameter, no output schema, and rich annotations, the description is complete. It names the return fields (platform, smb_id, channels, country), clarifies cost and safety, and situates the tool within the surrounding workflow. An agent has enough to invoke 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 input schema already documents the single url parameter with 100% coverage, including an example. The description does not materially add parameter-level semantics beyond classifying it as a booking URL, so the baseline score 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 uses a specific verb ('pre-flight check', 'classifies') tied to a concrete resource (booking URL) and names the downstream dependent tool (import_booking_url). It clearly differentiates itself from sibling tools like schedule_appointment by framing itself as a check that happens before any paid action.
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 when to use it: 'BEFORE calling import_booking_url + schedule_appointment' and why: to 'de-risk a paid booking'. It also states what it does NOT do ('WITHOUT fetching the page or spending money'), giving the agent clear usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Given criteria (vertical, location, capability, price band, availability window), return ranked candidate businesses from our supply network. THE NETWORK IS SMALL AND STILL MOSTLY SAMPLE DATA: entries that are not real are named [DEMO] and flagged is_demo - check that field before acting on a result. [free, no key]
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes | ||
| vertical | Yes | Service vertical to search within | |
| capability | No | Specific service capability required, e.g. 'haircut', 'plumbing',… | |
| price_band | No | ||
| max_results | No | ||
| availability_window | No | Accepted but NOT APPLIED - it does not narrow results. We do not hold live… |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by explicitly warning that the network is small and mostly sample data, and instructs the agent to check the is_demo field before acting. It also notes '[free, no key]' indicating no authentication required, which is useful context not present in annotations. Since annotations already declare readOnly and idempotent hints, the description adds value with the demo warning and free access.
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, with two sentences and a short tag. It front-loads the purpose and criteria, then adds the critical warning about sample data. Every sentence earns its place; 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?
For a search tool with no output schema, the description explains the output type (ranked candidates) and warns about data quality. It does not describe the structure of each candidate beyond the is_demo flag, but given the complexity of the input schema (nested objects), the description covers the key caveat. It also mentions availability_window as not applied, which is a significant behavioral note. A small gap: no mention of how ranking works, but that's likely acceptable.
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 50%, so description helps with some parameters. The description lists vertical, location, capability, price band, availability window as criteria, which adds clarity beyond the schema. However, it does not detail the format for nested objects like price_band or availability_window (though schema provides some info). It also flags that availability_window is not applied, which is critical and not in the schema description. Thus, description compensates well for the gaps.
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: return ranked candidate businesses from a supply network based on criteria. It lists specific filters (vertical, location, capability, price band, availability window) and the output type (ranked candidates). This distinguishes it from siblings like verify_business or check_compliance, which have different purposes.
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 implies when to use this tool (when searching for businesses), but does not explicitly state when NOT to use it or provide alternatives. However, it does mention the small network and sample data, which subtly warns about reliability. There is no explicit comparison to sibling tools, so the guidance is moderate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve the final OutcomeReceipt for a completed operation. [free, no key]
| Name | Required | Description | Default |
|---|---|---|---|
| operation_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds useful context beyond annotations: the operation must be completed, and the call is free with no key required.
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 tight sentence plus a bracket note. Every element earns its place, and the core purpose is front-loaded before the access note.
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 retrieval tool with strong annotations, the description is mostly complete: it identifies what to pass, when it is valid, and the access requirements. It does not describe the return shape, but no output schema exists and the resource name 'OutcomeReceipt' is reasonably self-descriptive.
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% and the schema only says operation_id is a required string. The description adds context by tying operation_id to the completed operation whose OutcomeReceipt is requested, but it does not specify where the ID comes from or its format.
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 ('Retrieve') and a specific resource ('final OutcomeReceipt') for a 'completed operation'. This clearly distinguishes it from siblings like get_status, which would naturally map to intermediate status rather than the final receipt.
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 clear context: this is for retrieving the outcome only after an operation has completed. It does not explicitly name alternatives or exclusions, but the completed-operation condition is a meaningful usage signal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Query the current state of any in-flight async operation by operation_id. [free, no key]
| Name | Required | Description | Default |
|---|---|---|---|
| operation_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description only needs to add context. It adds that the operation is free, requires no API key, and applies to in-flight async operations, which provides useful behavioral context beyond 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?
The description is compact and front-loaded. The primary purpose is stated in one clear sentence, and the cost/auth note is appended succinctly. Every element 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, one-parameter, read-only status tool, the description provides enough to call it correctly: the target resource, the identifier, and the cost/auth constraints. It does not detail the output shape or possible statuses, and it does not explain what happens if the operation is not in-flight, but these are not critical for a basic status query given the annotations.
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 only specifies 'operation_id' as a string with no description, so the description carries the semantic burden. It clarifies that operation_id references an in-flight async operation and that the tool queries its state, which gives the parameter meaningful context. It could be stronger by explaining how to obtain the operation_id, but it is adequate.
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 specifies a verb ('Query'), a resource ('the current state of any in-flight async operation'), and the key identifier ('operation_id'). It also implicitly differentiates from the sibling 'get_outcome' by focusing on in-flight operations rather than completed outcomes.
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 clear context: use this when you need the current state of an in-flight operation identified by operation_id. It also notes the operation is free and requires no key. It does not explicitly mention exclusions or alternatives, but the usage context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Turn ANY public booking URL (Cal.com, Calendly, Doctolib, Booksy, Fresha, OpenTable, Setmore, Square, Acuity, Schedulista, Squarespace, BookMyCity) into a callable smb_id you can immediately use with schedule_appointment, send_message, or capture_lead. Idempotent — calling twice returns the same smb_id. [free, requires key]
| Name | Required | Description | Default |
|---|---|---|---|
| vertical | No | Best-guess vertical. If omitted, inferred from the platform (e.g., Doctolib ->… | |
| booking_url | Yes | Full URL the user supplied. Must point at one of the 12 supported booking… | |
| capabilities | No | Free-form capability tags (e.g., ['haircut','color','blowdry']). | |
| country_code | No | ISO 3166-1 alpha-2 (e.g. 'US', 'FR'). Used for compliance routing on later… | |
| business_name | No | Optional override. If omitted, the business name is auto-extracted from the… | |
| contact_email | No | Optional. | |
| contact_phone | No | Optional. If omitted, the platform integration handles outreach. | |
| idempotency_key | No | Optional client-supplied key for safe retries. Replaying the same key within 24h returns the original receipt - the operation is NOT re-executed and NOT re-charged. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide idempotentHint, readOnlyHint, destructiveHint, but the description adds valuable context: it states idempotency explicitly ('calling twice returns the same smb_id'), mentions free tier and key requirement, and implies side effects (returns an smb_id). It also provides the behavior of being able to use the result with other tools. Since it adds meaningful context beyond annotations without contradicting them, score a 4.
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 but packs essential information: purpose, supported platforms, outcome, idempotency, and note about free/key. Every sentence earns its place. The critical info (what it does) is front-loaded, and the idempotency note and free requirement are brief but important. It avoids 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 the tool's complexity (8 params, 1 required) and full schema coverage, the description needs to provide enough context for an agent to call it effectively. It explains the main output and use case, and the idempotency behavior. However, it does not explain what happens on failure (e.g., unsupported URL) or how to interpret the returned smb_id beyond being reusable. Since there is no output schema, a bit more on the return value or error handling would be helpful, but it's not critical. Score 4.
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. The description itself does not explain individual parameters, but it explains the overall purpose and a key behavior (idempotency). However, it adds context to the booking_url parameter by listing supported platforms retaining the 12 platforms in the schema) and mentions optional overrides like business_name auto-extraction. Given the schema is already detailedais a plus, but the description could do more to clarify edge cases or parameter interactions.
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 clearly states it converts any public booking URL into an smb_id, lists supported platforms, and mentions idempotency. It distinguishes itself from siblings like schedule_appointment and check_booking_link by its specific action (importing a URL) and output (an smb_id that can be used with other tools). The verb 'import' plus the resource 'booking URL' is specific 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?
The description explicitly says the resulting smb_id can be used with schedule_appointment, send_message, or capture_lead, which tells the agent when to use this tool (when you have a booking URL and need an smb_id). It also notes it's idempotentandarerequires a key. However, it doesn't explicitly mention when NOT to use it or contrast with siblings like check_booking_link, so it loses a point.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return an expected cost estimate, latency estimate, and success-probability estimate for a proposed call before execution. Returns the exact price when it is fixed, and a min/max range when the cost depends on channel or outcome. It does not promise an accuracy percentage - check cost_range. [free, no key]
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes | The same request body you would pass to the operation | |
| operation | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral context beyond that: it returns exact prices when fixed, min/max ranges when variable, does not promise accuracy, and requires no API key ('[free, no key]'). No contradiction with 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 focused sentences with no filler. The first sentence front-loads the core purpose, the second explains the exact-vs-range behavior, and the third adds a crucial caveat plus auth note. 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?
The description covers what the tool returns, how pricing varies, and the free/no-key requirement. With no output schema, the return-value description is useful and mostly sufficient. Minor gaps remain around expected operation naming and the exact output shape, but the tool is simple enough that this is not a major deficiency.
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 documents params as 'the same request body you would pass to the operation,' and the description reinforces the 'proposed call' idea. However, the operation parameter is only a bare string with no allowed values or format, and the description does not elaborate on how operations are specified. Schema coverage is exactly 50%, so the description only partially compensates.
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 names a specific verb ('Return') and a precise resource: cost, latency, and success-probability estimates for a proposed call before execution. This clearly distinguishes it from siblings like get_outcome, get_status, or verify_company_record, which address different concerns.
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 clearly signals this tool is for pre-execution estimation ('before execution') and cautions that accuracy is not promised, directing the user to cost_range. It does not explicitly name alternatives or state when not to use it, but the context is clear enough given the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Availability lookup, hold, confirm, reschedule, or cancel appointments with an SMB. Routes through the SMB's native booking system if available, falls back to voice AI or web form. [from $0.15/call, variable] [async→get_outcome]
| Name | Required | Description | Default |
|---|---|---|---|
| notes | No | ||
| action | Yes | ||
| smb_id | Yes | ||
| service | No | ||
| customer | No | ||
| requested_time | No | ||
| idempotency_key | No | Optional client-supplied key for safe retries. Replaying the same key within 24h returns the original receipt - the operation is NOT re-executed and NOT re-charged. | |
| existing_appointment_id | No | Required for reschedule/cancel |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true and readOnlyHint=false, so the description doesn't need to restate that. It adds useful behavioral context: routing through native booking system, fallback to voice AI/web form, cost per call, and async completion via get_outcome. It also notes idempotency behavior in the schema, which is a strong behavioral disclosure.
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-loaded with the core purpose, then adds routing, cost, and async notes. Every sentence earns its place, though the cost and async notes could be seen as secondary. It is appropriately sized for a tool with 8 parameters and complex behavior.
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 (8 params, nested objects, multiple actions, async behavior), the description covers the key operational aspects: routing, fallback, cost, and async completion. It doesn't explain return values, but there is no output schema and the async note points to get_outcome. The main gap is lack of explicit guidance on which parameters apply to which actions, but the schema's existing_appointment_id description partially covers that.
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 only 25%, so the description must compensate. It does mention the action types and the routing behavior, and the schema itself documents idempotency_key and existing_appointment_id. However, the description doesn't explain the requested_time structure, customer object, or service field beyond what the schema shows. Still, the description adds meaningful context for the core action parameter.
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 names a specific verb set (lookup, hold, confirm, reschedule, cancel) and a resource (appointments with an SMB), and it distinguishes the tool from siblings by noting it routes through the SMB's native booking system, voice AI, or web form. It clearly covers the action enum and the tool's 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?
The description states when to use the tool (for appointment operations with an SMB) and gives context about routing behavior, but it does not explicitly say when not to use it or name alternatives. Sibling names like check_booking_link and import_booking_url imply related but different use cases, yet the description doesn't explicitly exclude them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Service health probe: runs 6 internal checks and reports how many passed. Confirms the server is up and responding - it does NOT probe each tool individually. Use to verify connectivity before production use. [free, no key]
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds value by disclosing the internal check count (6), the aggregate pass/fail nature, and the free/no-key requirement, which are not in 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?
The description is compact and front-loaded: it states the core function first, then the limitation, then the use case, then the free/no-key note. Every sentence earns its place 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 zero-parameter, read-only health probe with no output schema, the description covers the essential information: what it checks, what it reports, what it does not do, and when to use it. The only minor gap is not describing the exact output format, but that is not critical for a simple health probe.
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 schema is trivially complete. The description adds no parameter details because none are needed; the baseline of 4 for zero-parameter tools 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 clearly states the tool's function: it runs 6 internal checks and reports how many passed, confirming the server is up. It explicitly distinguishes itself from per-tool probing, which differentiates it from sibling tools like get_status or verify_company_record.
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 says to use it to verify connectivity before production use, which gives a clear context. It does not explicitly name alternative tools or state when not to use it, but the 'does NOT probe each tool individually' exclusion provides useful guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Look up what we know about a business in our supply network: its contact channels, capabilities, and when the record was last verified. This is a DIRECTORY LOOKUP - it does not contact the business. [free, no key]
| Name | Required | Description | Default |
|---|---|---|---|
| smb_id | Yes | ||
| capability_to_verify | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate read-only and idempotent behavior. The description adds value by clarifying this never contacts the business and that the data reflects a stored record ("when the record was last verified"). This is useful context beyond 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?
The description is two concise sentences, front-loaded with the core action and output, followed by a clarifying behavioral note. No filler or redundant detail.
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 names the returned data categories (contact channels, capabilities, last verified timestamp). It sufficiently sets expectations for a simple lookup tool, though it could clarify the optional capability parameter's role.
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 0%, so the description carries the full burden for parameterscy. It mentions 'a business' and 'capabilities' but does not explicitly explain what `smb_id` should contain or how `capability_to_verify` affects the lookup. The optional parameter's meaning remains ambiguous.
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 is for looking up known business information in the supply network, with specific outputs named (contact channels, capabilities, last verified record). The explicit 'DIRECTORY LOOKUP - it does not contact the business' removes ambiguity about whether this is a live verification or a passive query.
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 clear usage context: it is a read-only directory lookup, and explicitly says it does not contact the business. It does not name alternative sibling tools for comparison, but the exclusion is enough to prevent obvious misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
check_booking_link1 field changedInput schema / properties / url / descriptionPrevious value: -"Full http(s) URL to classify, e.g. 'https://cal.com/jane' or 'https://www.opentable.com/r/acme'."New value: +"Full http(s) URL to classify, e.g. 'https://cal.com/jane' or…"find_business2 fields changedInput schema / properties / availability_window / descriptionPrevious value: -"Accepted but NOT APPLIED - it does not narrow results. We do not hold live calendars for the supply network. The response carries availability_window_applied: false when you send one. To book a specific slot use schedule_appointment with requested_time, which checks real availability."New value: +"Accepted but NOT APPLIED - it does not narrow results. We do not hold live…"Input schema / properties / capability / descriptionPrevious value: -"Specific service capability required, e.g. 'haircut', 'plumbing', 'tax_consultation'"New value: +"Specific service capability required, e.g. 'haircut', 'plumbing',…"import_booking_url4 fields changedInput schema / properties / booking_url / descriptionPrevious value: -"Full URL the user supplied. Must point at one of the 12 supported booking platforms; auto-detected from the host."New value: +"Full URL the user supplied. Must point at one of the 12 supported booking…"Input schema / properties / business_name / descriptionPrevious value: -"Optional override. If omitted, the business name is auto-extracted from the page's <title> or og:title."New value: +"Optional override. If omitted, the business name is auto-extracted from the…"Input schema / properties / country_code / descriptionPrevious value: -"ISO 3166-1 alpha-2 (e.g. 'US', 'FR'). Used for compliance routing on later send_message calls."New value: +"ISO 3166-1 alpha-2 (e.g. 'US', 'FR'). Used for compliance routing on later…"Input schema / properties / vertical / descriptionPrevious value: -"Best-guess vertical. If omitted, inferred from the platform (e.g., Doctolib -> healthcare, OpenTable -> restaurants)."New value: +"Best-guess vertical. If omitted, inferred from the platform (e.g., Doctolib ->…"check_booking_linkfind_businessget_outcomeget_statusimport_booking_urlpreview_costschedule_appointmentself_testverify_businessVerified local businesses, bookable by AI agents: services, prices, availability and appointments.
Discover and book businesses via AI agents.
Agentic CRM for service businesses — bookings, customers, WhatsApp, loyalty, invoicing.
Find local services, check live availability, and book real appointments with consent.
Add one secure layer between your agents and this server.
