workspace

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

With no annotations provided, the description carries the behavioral disclosure burden. It states that answers are published and multilingual, which implies a read-only retrieval operation and gives useful content expectations. It does not mention pagination, ordering, or errors, but for such a simple FAQ lookup the provided context is reasonably sufficient.

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 with no wasted words. The core scope is front-loaded, and the multilingual note is placed after, making the structure easy to parse 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?

For a tool with one optional parameter, no output schema, and no annotations, the description plus schema is nearly complete: it explains what the tool returns, the optional location filter, and language variants. It does not describe the exact response shape, but that is not critical for such a straightforward FAQ endpoint.

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 parameter is fully documented as 'Location slug; omit for the general questions.' The description only restates the optional narrowing behavior without adding new parameter-level detail, so it appropriately falls at the baseline for high schema coverage.

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 identifies the resource as published questions and answers about Floreal Holidays and notes optional location narrowing, which makes the tool's purpose unambiguous. It lacks an explicit action verb like 'retrieves' or 'lists,' but it is still distinct from sibling tools such as get_menu, get_stay_price, and list_locations.

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 clear context: this tool serves FAQ content about Floreal Holidays and can be limited to a specific location through an optional parameter. It does not explicitly discuss when to avoid this tool or point to alternatives, but the scope is clear enough for an agent to select it appropriately.

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 provided, the description carries the full burden. It discloses that results are 'current,' location-published, and not guaranteed to exist, which is meaningful behavioral context. It does not state what happens for locations without menus or describe the return format, leaving some uncertainty.

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 a single tight sentence plus a one-sentence caveat, with no filler or repetition. The key availability limitation is stated directly and front-loaded enough that an agent will notice it.

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 retrieval tool, the description covers the core context: what is returned, for which kind of location, and the important caveat that menus are not universally published. There is no output schema, so a bit more detail about the response format would improve completeness, but the essential invocation context is present.

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?

Parameter schema coverage is 100%, so the schema already documents both parameters, including the domain slug example and the language enum with a default. The description adds little beyond 'one Floreal location,' which maps to the domain parameter, so it provides no substantial extra parameter semantics.

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 resource (restaurant and food & beverage menus) and its scope (one Floreal location), and highlights a key limitation: not every location publishes menus. It lacks an explicit verb like 'gets' or 'returns,' and it does not explicitly contrast itself with sibling tools, so it stops just short of 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?

The description implies that this tool should be used to retrieve menus for a single specific Floreal location, and the 'Not every location publishes menus' caveat is useful context. However, it gives no explicit guidance on when to prefer this over sibling tools or what to do when a location does not publish menus.

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 are present, so the description carries the full behavioral burden. It discloses that the price is live, that it covers all-in price and availability, and that the answer includes a bookingUrl that should always be shared. This goes beyond the schema and helps the agent understand what the result is for and what to do with it. It does not specify the exact response shape, but the core behavior is clearly conveyed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences with no filler. It front-loads the core purpose, then adds the package-specific variant, a critical instruction about bookingUrl, and the alternative tool for the un-located scenario. 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?

For a tool with 8 parameters and no output schema, the description covers the essential context: scope, input intent, the special packageId path, the bookingUrl output behavior, and when to route to search_stays. It does not spell out every parameter, but the schema already does that. The absence of any annotation is compensated by the concrete behavioral and usage details in the description.

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 adds extra meaning beyond the schema by explaining that packageId comes from list_arrangements and that the parameters collectively describe a 'party' for a stay. This helps the agent understand the relationship between parameters and the intended use, not just their individual formats.

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 ('Live all-in price and availability') on a clear resource (a stay at one Floreal location) and specifies the key qualifiers (arrival date, nights, party, per accommodation type). It also distinguishes itself from search_stays by noting that this tool targets a single location, removing ambiguity about which sibling to pick.

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 to use search_stays instead when no location has been chosen, and tells the agent to pass a packageId from list_arrangements to price a specific package. This gives clear when-to-use and when-not-to-use guidance plus a named alternative.

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 are provided, so the description carries the full burden of behavioral disclosure. It correctly characterizes the operation as informational and adds the non-obvious fact that gift cards are valid at every location. It doesn't specify whether the response is a list, but for a zero-parameter info tool this is a minor gap.

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, each with a distinct job: the first defines the tool's scope, the second adds a relevant validity fact. There is no filler, repetition, or unnecessary 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?

For a zero-parameter, read-only info tool with no output schema, the description covers all essential details an agent needs to decide to call it and interpret the result. The included topics plus the validity fact make the tool self-explanatory.

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?

There are zero parameters, so the schema imposes no burden. The description orients the agent to the content domains (amounts, languages, where to buy) that the tool will return, effectively substituting for parameter documentation.

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 'Information about Floreal Holidays gift cards' and enumerates the specific aspects covered: amounts, languages, and where to buy. This makes it immediately distinguishable from sibling tools like get_faq or get_menu, none of which deal with gift cards.

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?

There is no explicit 'use this when' wording, but the description makes the context obvious: any question about Floreal gift card amounts, languages, or purchase locations. Since no sibling tool overlaps with gift card topics, no exclusions or alternatives are needed.

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 provided, the description carries the behavioral burden. It discloses that prices are only indicative samples, that a location can combine multiple accommodation kinds, and that a real quote requires get_stay_price. This prevents the agent from treating sample prices as authoritative, though it could have further explained empty/error 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?

The description is front-loaded with the core purpose and then efficiently layers use cases, a combinability caveat, and the cross-reference to get_stay_price. Every sentence adds information and the overall length is appropriate for the tool's complexity.

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 list tool with no output schema, the description adequately communicates the return content (accommodation kinds with indicative prices) and the key caveat. The required 'domain' parameter is documented in the schema, but the description does not explicitly mention that invalid or unknown location slugs may yield empty results, which would round out 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 description coverage is 100%, so the baseline is 3. The description reinforces that prices are sample-based, which aligns with the 'arrival' parameter's sample nature, but it does not add meaningful new parameter semantics beyond what the schema already states for 'domain' and 'arrival'.

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 ('list') and resource ('accommodation types of a Floreal Holidays location'), then enumerates example categories to make the scope concrete. It also answers the exact user questions the tool is for ('does Blankenberge have hotel rooms?'), making it easily distinguishable from sibling tools like get_stay_price.

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 states when to use the tool: 'Use this for questions about what a location has,' with two concrete example questions. It also gives a clear when-not-to-use directive by pointing to get_stay_price for real-date pricing, which routes the agent to an alternative.

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 transparency burden. It discloses what the list contains (name, description, validity period) and importantly states that prices are not included because they depend on stay and party, directing the agent to get_stay_price. It does not explicitly state read-only behavior or pagination/error behavior, but for a simple listing tool this is reasonable coverage.

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 with no filler. The first sentence front-loads the purpose and content; the second adds a valuable workflow note about using get_stay_price. 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?

For a one-parameter tool with no output schema, the description adequately explains what is returned, the scope, and the critical exception that prices must be requested separately. Minor missing details such as exact return shape or pagination are not significant for this simple list operation.

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 fully documents the sole parameter 'domain' as a location slug with an example, giving 100% coverage. The description only reinforces this with 'one location' and does not add additional parameter syntax, format constraints, or examples beyond what the schema already provides.

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 the resource: 'bookable packages of one location: stay arrangements and add-on extras, with name, description and validity period.' It distinguishes itself from the pricing sibling by directing price requests to get_stay_price, and its focus on packages/add-ons separates it from list_accommodation_types.

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 for when to use the tool: to get the bookable packages of a single location. It also instructs the agent to follow up with get_stay_price using the packageId when a price is needed. It lacks explicit exclusions for other sibling tools, so it misses a 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?

With no annotations provided, the description carries the full disclosure burden. It reveals the scope ('all parks'), the output fields (name, type, town, coordinates), the geographic coverage, and a key semantic nuance about 'type' vs accommodation. It does not specify the exact output format or coordinate format, but for a simple zero-parameter list tool this is sufficient transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: the core statement comes first, followed by a clarifying distinction and then practical usage guidance. Every sentence adds distinct value, and there is no repetition of the tool name or title.

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 listing tool, this description is complete. It specifies what data is returned, the geographic scope, the meaning of a potentially ambiguous field, and how the results should be used with sibling tools. No output schema exists, but the description adequately compensates by naming the returned fields.

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?

There are no parameters, so the input schema is fully covered by its empty properties. The baseline for zero-parameter tools is 4; the description appropriately focuses on output semantics rather than parameters, and it adds useful context about the slug usage that relates to how the returned data will be consumed.

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 exactly what the tool returns: all Floreal Holidays holiday parks in Belgium with name, type, town and coordinates. It also clearly differentiates this from list_accommodation_types by explaining that 'type' refers to the kind of site, not accommodation, so an agent cannot confuse the two tools.

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 tells the agent when not to use this tool for accommodation details and names the alternative: 'ask list_accommodation_types for that.' It also provides concrete downstream guidance, instructing the agent to use the name as a slug for the `domain` argument of other tools, which makes the tool's role in a workflow unambiguous.

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 behavioral disclosure burden. It reveals that results are live, include all-in prices, are sorted cheapest first, and carry a bookingUrl that should always be shared. It does not cover edge cases like no availability, but the core runtime behavior is clearly disclosed.

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?

Every sentence earns its place: scope, usage timing, example queries, narrowing options, result behavior, and the sibling alternative. The core purpose is front-loaded and the description remains readable despite covering several useful details.

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 10 parameters, no output schema, and no annotations, the description still explains when to use the tool, how to narrow the search, what the results look like, and how to follow through with the bookingUrl. Required parameters are left to the schema, which fully documents them, so nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds light semantic color by showing example values for region and accommodation and clarifying maxPrice as a filter, but most parameter meaning is already fully documented in 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?

The description uses a specific verb and resource: 'Find where Floreal Holidays has a stay available' across every location. It clearly distinguishes this tool from get_stay_price by noting the all-locations scope and explicitly naming the sibling for known single locations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states when to use: 'whenever the guest has not picked a location yet', and provides concrete example queries. It also tells the agent when not to use it: 'For one known location get_stay_price is faster.' This is strong routing guidance.

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