Jenesis Travel

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

Annotations already indicate a safe read-only, idempotent operation. The description adds meaningful context by clarifying the result is 'Indicative' and 'Not a quote,' and discloses the scope of Jenesis's planning styles, which helps set expectations about the nature and applicability of the output.

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 short, information-dense sentences. Every sentence earns its place by adding either a disclaimer ('Not a quote'), a scope definition, or the source of the estimate.

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?

Despite having five parameters and no output schema, the description does not explain the output format (e.g., total vs. per person, currency units beyond 'USD'), nor does it clarify the meaning of parameters like region or inclusions. The dataset implications are under-specified for a tool of this 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 0%, so the description must compensate, but it provides no direct explanation of any parameter. The phrase 'Mid-range to ultra-luxury' subtly maps to the style enum, yet nights, travelers, region, and the optional inclusions array remain completely unaddressed.

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 tool's intent is clear from the title and the description's reference to a budget calculator producing a USD range. It is distinct from sibling tools like list_journeys or start_enquiry, though the description itself doesn't explicitly name a verb like 'estimates' or 'calculates'.

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 use for mid-range to ultra-luxury trip planning via 'Mid-range to ultra-luxury is what Jenesis plans,' and 'Not a quote' hints it shouldn't be used for binding quotes. However, no explicit when-to-use, when-not-to-use, or alternatives to sibling tools are provided.

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 disclose the safe, read-only, idempotent nature. The description adds behavioral context by positioning this as the first call in the workflow and explaining handling of the WhatsApp URL. It does not contradict any annotation.

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 only two sentences, front-loaded with the core fact list, then a clear usage directive and conditional action. Each sentence contributes value 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 lookup, the description sufficiently explains what facts are returned and the follow-up action for human contact. Given the simple scope and strong annotations, no essential information 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 tool has zero parameters, so the schema provides complete coverage. The description adds no parameter details, but none are required; the baseline for 0 parameters is 4.

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 identifies the tool as providing company facts for Jenesis Travel, listing specific content (licence, contact, WhatsApp, enquiry-led model). This specific verb+resource pairing distinguishes it from sibling tools like get_journey and list_faqs.

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 instructs 'Call this first,' establishing when to use the tool relative to other actions. It also gives a conditional directive ('If the user wants a real person, share the WhatsApp URL'), providing actionable guidance beyond the basic purpose.

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 clear. The description adds the qualifier 'published' (only published resources), which is useful, but it does not disclose other behaviors such as error handling or whether currency affects output. With rich annotations, the description contributes modestly.

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 long, front-loaded with the primary action, and contains no filler. Every word contributes to understanding the tool's scope and usage.

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?

This is a simple get-by-slug tool with strong annotations and no output schema. The description covers the core purpose and the main alternative. It falls short only in not explaining the currency parameter or potential edge cases, but for its simplicity, it is largely complete.

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 must compensate. It explains 'by slug' for the slug parameter, which is helpful for the required field, but the optional currency parameter is not mentioned at all. The enum in the schema provides some self-explanation, but the description adds limited parameter-level context.

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 retrieves a single published journey, residence, group programme, or package by slug. It uses a specific verb ('Get') and resource list, and distinguishes itself from sibling list_journeys by specifying '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?

The description explicitly directs users to list_journeys when the slug is unknown, providing a clear when-to-use alternative. This is strong guidance for tool 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?

Annotations already declare read-only and idempotent behavior. The description adds the behavioral detail that only published FAQs are returned, and that filtering by pillar or search text is supported, going beyond the structured 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?

A single, well-structured sentence that immediately states what the tool does and its key optional filters. No wasted words.

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 listing tool with three optional parameters and no output schema, the description conveys the core behavior and filters. It omits details like limit and return structure, but the simplicity and annotations make it sufficient for an agent.

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 must compensate. It explains the semantics of 'pillar' and 'q' (search text), but does not mention the 'limit' parameter, leaving a gap for one of three 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 lists published FAQs from the Jenesis CMS, with optional filters. The verb 'list' and resource 'FAQs' are specific, and it is distinct from sibling tools (journeys, budget, company, enquiry).

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 clearly indicates this is for retrieving published FAQs, and mentions optional filters for pillar and search text. It does not explicitly contrast with alternatives, but the sibling tools are obviously different in purpose, providing clear context.

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 readOnly/idempotent/non-destructive. The description adds 'Live CMS data' (real-time source) and 'Enquiry-led' (data nature), which are useful behavioral traits 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?

Two sentences, front-loaded with purpose, no redundant wording. Every phrase earns its place, making it highly concise and well-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?

No output schema exists, so the description's 'List' implies a list result but doesn't specify format or pagination. The purpose is clear and the context (live CMS, enquiry-led) helps, but missing param semantics reduce completeness.

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 has 0% description coverage. The description implicitly explains the 'kind' enum by listing journeys, residences, group programmes, and packages, but the 'q' and 'limit' parameters receive no semantics. Description partially compensates but not 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 resource types (journeys, residences, group programmes, packages) with a specific verb 'List'. It distinguishes from sibling tools like get_journey (single) and list_faqs by naming the full 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?

'Enquiry-led — not a booking inventory' provides explicit context on when to use (enquiries) and when not (bookings). However, no specific alternative tool is named, so it falls short of full 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?

The description adds valuable behavioral context beyond the annotations: the 4-hour cooldown per email, the explicit warning against retrying after success, and the clarification that the tool does not reserve hotels or take payment. These details disclose non-obvious side effects and constraints, fully complementing the annotated flags (readOnlyHint=false, 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?

The description is four sentences long, every sentence earns its place, and the most critical information is front-loaded. It avoids fluff and redundancy, making it easy for an agent to parse and act on quickly.

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 (18 parameters, no output schema), the description covers usage prerequisites and side effects well but leaves a significant gap: it does not explain what data should be collected for the enquiry or what the response contains. This makes the description sufficient for basic invocation but incomplete for fully autonomous handling of this complex 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?

With 18 parameters and 0% of them described in the tool description, the burden falls on the description to explain at least the key parameters. It mentions 'name' and 'email' as prerequisites, but does not clarify the required 'enquiryType' field or any of the optional ones. The schema enums help, but the description does not compensate for the lack of semantic guidance.

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 with a specific verb and resource: 'File a planning enquiry with Jenesis Travel.' This distinguishes it from sibling tools like list_journeys or estimate_budget, which are about browsing or estimating rather than starting a service request.

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 explicit preconditions ('Call only after the user confirmed name, email, and that they want Jenesis to reply'), a clear exclusion ('If they would rather talk to a person now, share WhatsApp instead of calling this tool'), and a rate-limiting rule with a do-not-retry instruction. This is exemplary usage guidance.

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