Kipra Rent A Car

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

In the absence of annotations, the description provides critical behavioral context that a machine agent needs: 'Data is live from the booking engine — never cached or invented.' It also clarifies that prices include insurance and VAT, setting expectations about the returned values beyond just the numeric total.

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 and highly informational, front-loading the critical functional aspects (live data, availability, pricing). While slightly verbose, every sentence conveys essential, non-redundant value for the agent.

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 is exceptionally complete for a real-time search tool. It covers the geographic scope, the data integrity (live), the content of the results (cars, prices, booking URLs), and the financial inclusion (VAT/Insurance), giving the agent everything it needs to confidently invoke the 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?

The description adds specific geographical and operational meaning that the schema misses, such as specifying 'Cyprus local time' and detailing that EUR and TRY are always included even if another currency is requested. This clarifies the boundaries of the `currency` and timestamp parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool is for North Cyprus car rental availability and explicitly mentions it returns actual available cars with specific financial data (prices, tax inclusion, booking link). While it doesn't name every sibling it replaces, its function is clearly defined for a live search operation.

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 usage by highlighting its 'live' nature, which suggests a difference from potentially static price lists or general availability lookups provided by siblings like get_booking_link or list_prices. It defines the core function of checking availability for a window.

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

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

With no annotations, the description carries the burden well: it discloses that one call returns every available topic, that content is staff-written English requiring downstream translation, and that answers must be grounded strictly in returned text. It doesn't state explicitly that the tool is read-only or describe the return structure, which keeps it short of a 5.

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 dense paragraph, front-loaded with what the tool contains before moving to agent instructions. The topic inventory is long but earns its place for scoping; the embedded WhatsApp number and translation instruction are borderline but still actionable.

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-required-parameter read tool with no annotations and no output schema, the description covers purpose, coverage, and grounding rules thoroughly. What it leaves out is the shape of the returned content (sections, single blob, length), which would help an agent plan its answer.

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 both parameters are enums, so the schema already defines topic and language fully. The description reinforces that topic can be omitted ('one call returns every available topic'), but the remark that 'Texts are staff-written English; translate onward' is in mild tension with the language enum's claim to control label language, adding ambiguity rather than clarity.

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 resource (staff-written company knowledge base for a North Cyprus car rental service) and enumerates exactly what it covers: contact/hours, locations, rental terms, insurance/deposit, driver requirements, payment, FAQ. The scope is clearly disjoint from siblings like list_prices, check_car_availability, and get_booking_link.

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 triggering condition: 'Use it for ANY question about the company, its rules or its services,' plus a when-not fallback (if the text doesn't cover it, point the visitor to the Kipra team via WhatsApp). It does not explicitly name sibling tools or say 'for prices use list_prices,' so routing against alternatives is left to inference.

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 does real work: it discloses that the tool only builds a URL (no booking is made server-side), that the transaction happens on the site with no credit card, no deposit, and free cancellation. The main gap is that it says nothing about URL lifetime or whether dates outside booking hours cause an error versus a degraded link.

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 with the deliverable front-loaded, then the handoff consequence, then the one non-obvious parameter rule. Nothing is repeated from the schema and no sentence is 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 four-parameter URL builder with no output schema, this is nearly complete: what it returns, what happens next, and the language rule are all covered. The only missing piece is failure behavior for invalid or out-of-hours dates, which the schema hints at but never explains.

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 schema already documents all four parameters including enums and the date-time pattern. The description adds only a small bit of meaning — that 'lang' should match the visitor — and says nothing about 'currency' or about the booking-hours constraint beyond restating the 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 and deliverable ('Builds a prefilled ... booking URL') plus the exact domain/path of the URL produced. An agent can immediately tell this is URL-construction, not a booking action or an availability/pricing lookup like its siblings.

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?

Usage is implied rather than stated: 'The visitor picks a car and confirms' tells the agent the flow is handed off, and the language-matching instruction gives a situational rule. But it never says when to use this versus check_car_availability or list_prices, nor whether availability should be confirmed first.

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

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

With no annotations, the description carries the burden; it does establish that rates are 'current' (not historical) and read-only by omission of any mutation. It does not disclose rate source, refresh cadence, or caching, and the payment-acceptance sentence is business context rather than operational detail.

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, front-loaded with the resource and its scope. The second sentence is mild supplementary context rather than waste, though it partially repeats the currency list.

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 the description does not say what the return shape looks like (e.g. one rate per currency against EUR) or whether a timestamp accompanies the rates. For a simple zero-param read tool this is adequate but leaves a real gap around freshness and response structure.

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?

Zero parameters, so there is no parameter documentation burden and the baseline of 4 applies. The description correctly frames the fixed currency set (EUR base, TRY/USD/GBP quotes) that would otherwise be an unknown implicit scope.

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?

Names a concrete resource with explicit scope: current EUR-base exchange rates for TRY, USD and GBP. An agent immediately knows what data comes back. It does not differentiate from the loosely adjacent sibling list_prices (which could also surface currency figures), so not a 5.

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?

Usage is implied by 'used by the booking engine for display conversion', and the note that payment is accepted in all four currencies 'with no conversion markup' hints that conversion is only needed for display, not payment. However, no explicit when-to-use/when-not or named alternative is given.

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 carries the load, and it does disclose non-obvious traits: prices already include insurance and VAT, amounts marked *_quoted are currency-dependent, and the agent must not perform conversions itself. It leaves return shape and whether data is cached/live unstated, which keeps it short of a 5.

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 purpose and the 'no dates' scope come first, then the content breakdown, then the currency rule and the sibling redirect. Dense but no sentence 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?

There is no output schema, so the description must convey return values — it does, listing rate ranges, tier structure, add-on pricing, and location fees, plus the VAT/insurance inclusion. That is everything needed to call and interpret this 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 coverage is 100% and each enum parameter is documented in the schema, including the default-language heuristic, so the baseline is 3. The description adds only the 'never convert yourself' constraint on currency, largely restating what the schema already says.

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?

Names a specific resource (current price list) and enumerates exactly what it contains: daily rate ranges per category and rental-length tier, add-on prices per day, and one-time location fees. It also explicitly excludes date-based pricing, which separates it from check_car_availability.

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?

States the select/no-select condition plainly ('without dates') and names the alternative with its trigger: 'For the total price of a specific window use check_car_availability instead.' An agent can route between the two without opening either schema.

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

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

With no annotations, the description carries the burden and does disclose meaningful behavior: the result echoes searched_from, which should be surfaced as a changeable assumption, and known error codes have a prescribed handling path. It leaves the side-effect profile (read-only) and result breadth implicit, so it is strong but not complete.

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 core capability, then layers required-parameter and error-handling instructions in short sentences that each carry operational value. Slightly dense but 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 five-parameter search tool with no output schema, the description covers the critical unknowns: the mandatory duration, the assumption surfaced via searched_from, and the error path. Enum semantics for category/currency/language are left entirely to the schema, which is acceptable at 100% coverage.

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 all five parameters are already documented in the input schema, which sets the baseline at 3. The description reinforces the required duration_days and the omit-to-search-from-now behavior of earliest_pickup_at, but adds no new meaning for category, currency, or language.

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 — finds the soonest window a rental car is free for a given number of days — with the search origin defined (now or an optional earliest pickup). This scope is distinct from check_car_availability, though the description never names that sibling to make the contrast 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?

Gives concrete procedural guidance: duration_days is required and the agent should ask the person if unstated, and on an error code such as earliest_in_past it should relay the reason and ask again rather than guessing a date. It stops short of naming when to prefer a sibling tool over this one.

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