Sporthotel IDEAL Hochgurgl

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

Annotations already establish that the call is read-only, idempotent, non-destructive, and open-world. The description adds useful behavioral context: suggestions are calculated live and each result includes a ready-made booking link, which helps the agent set expectations about output and freshness.

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 focused sentences: the first explains what the tool does, the second when to use it, and the third what the results contain. Every sentence earns its place, and the most important information is front-loaded.

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 rich annotations, full schema coverage, and an existing output schema, the description provides everything an agent needs to decide when to call the tool and what to expect. It also explains the fallback trigger and the live booking-link behavior, making the definition complete for its 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 coverage is 100%, so the schema already documents all five parameters. The description adds contextual meaning by framing check_in and check_out as the occupied desired period, but it does not add substantial parameter-level detail beyond what the schema already provides, so the baseline 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 states a specific action: searching for immediately bookable alternative dates around an occupied desired period. It details the kinds of alternatives (same arrival with different duration, same stay shifted by a few days) and clearly distinguishes the tool from the sibling verfuegbarkeit_pruefen by describing its fallback role.

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 call this tool whenever verfuegbarkeit_pruefen returns nothing, and positions it as the alternative to simply declining the guest. This gives clear when-to-use guidance and names the related sibling, leaving no ambiguity about the tool's place in the flow.

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, covering the safety profile. The description adds the useful behavioral detail that the tool returns the complete text rather than a snippet or summary, but it does not disclose potential errors or edge cases. This is acceptable given the strong annotation 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?

The description is a single, compact sentence that immediately communicates the action and the required input source. There is no redundant content; every word contributes to the meaning.

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 tool with an output schema and comprehensive annotations, the description is complete. It tells the agent what the tool returns, where the ID comes from, and the read-only nature is already covered by annotations. 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%, and the sole parameter 'id' is already documented as 'id aus einem search-Treffer'. The tool description essentially repeats this same semantic, so it adds little beyond what the schema already provides. Baseline 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 states a specific verb ('Liefert') and a specific resource ('den vollständigen Text zu einer id aus search'), making the tool's function immediately clear. It also distinguishes itself from the sibling 'search' by indicating that it delivers the full text for a search hit ID, not the search results themselves.

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 implies the correct usage context: the tool is meant to be called with an ID obtained from 'search'. It provides enough context to route an agent from search results to this full-text retrieval step, though it does not explicitly name alternatives or state when not to use it.

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, openWorldHint, idempotentHint, and non-destructive behavior. The description adds meaningful behavioral context: answers are grounded in a hotel-maintained knowledge base, and the agent must not fabricate content when the database has no entry. This goes 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?

Two sentences with no filler: the first states the core function and scope, the second gives a clear usage rule. The most important information is front-loaded.

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 tool is simple, annotations cover safety and idempotency, both parameters are fully described in the schema, and an output schema exists. The description additionally covers the fallback behavior when no knowledge entry exists, making it complete for an agent to use 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?

Schema description coverage is 100%, with both 'lang' and 'frage' already documented in the input schema. The description does not add parameter-specific meaning beyond that, so the baseline 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 ('Beantwortet') and a clear resource ('Wissensdatenbank'), scopes the tool to factual questions about the house, and lists concrete topics such as breakfast, pets, parking, and cancellation. The instruction 'Immer hier nachsehen' clearly marks it as the dedicated tool for this purpose, distinguishing it from generic siblings like search or hotel_info.

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 always check this tool before answering such questions, which is strong when-to-use guidance. It also adds a negative rule: do not invent answers when nothing is stored. It does not name specific alternatives or exclusion cases, but the context is clear enough.

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 mark this as read-only, open-world, idempotent, and non-destructive, so the safety profile is covered. The description adds valuable behavioral context by stating that results include booking links and by explicitly ruling out daily price data.

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 dense sentences with zero filler. The core result set is front-loaded first, and the critical exclusion plus sibling pointer appears immediately after, making it easy for an agent to scan.

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 and no output schema, the description communicates the main output categories and a key limitation. It does not detail the exact response structure, but the level of detail is adequate for an agent to decide whether to invoke it.

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 only parameter, 'lang', is fully documented in the schema with examples ('de, en, it, fr'), so the schema carries the semantic weight. The description adds no additional meaning about the language parameter, but given 100% schema coverage, the baseline 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 ('Liefert') and names three concrete resource types: Stammdaten des Hauses, Zimmerkategorien, and Pauschalen. It also explicitly excludes daily prices, distinguishing it from the sibling verfuegbarkeit_pruefen.

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 states what the tool does NOT provide ('KEINE tagesabhängigen Preise') and explicitly directs the agent to the correct alternative ('dafür verfuegbarkeit_pruefen verwenden'). This gives both a positive use case and a when-not-to-use condition.

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, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds a valuable behavioral boundary by stating that prices are not delivered here but by verfuegbarkeit_pruefen, preventing misuse. It also clarifies the scope of the explanation, and an output schema exists so return structure does not need to be described.

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 yet information-dense: it packs the core purpose, covered topics, example questions, and a sibling distinction into two sentences. Every clause adds actionable guidance and nothing is redundant with schema or annotations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only information tool with one optional parameter, an output schema, and comprehensive annotations, the description covers all agent-relevant aspects: what is explained, what questions are answered, and what is explicitly left to another tool. No critical gap is apparent.

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 only parameter, lang, is already fully documented in the schema as 'Sprachcode, z. B. de, en, it, fr', so the description does not need to repeat it. The description adds no extra parameter nuance, but since schema description coverage is 100%, 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 ('Erklärt') and names a precise resource ('online buchbaren Raten'), then enumerates exactly what is covered: basis of each rate, included services, cancellation/deposit terms, and child discounts. It explicitly differentiates itself from verfuegbarkeit_pruefen by stating that prices are provided there, so an agent can distinguish it from 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?

It provides concrete example queries ('Was ist in der Halbpension enthalten?', 'Wie kann ich stornieren?') that signal exactly when to invoke the tool. It also names verfuegbarkeit_pruefen as the source of prices, giving a clear exclusion for pricing questions. It does not contrast itself with other siblings like zusatzleistungen or hotel_info, so it stops short of full when-not-to-use guidance.

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, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral value beyond the annotations by disclosing the return shape (Treffer mit id, Titel und Link) and the intended follow-up action via fetch, plus the limitation regarding prices and availability.

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 with no filler. It front-loads the core purpose, then packs return format, next step, and exclusion into a compact, readable structure. 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 simple search tool with one parameter, rich annotations, and an output schema, the description covers the essential context: what is searched, what the results look like, how to proceed, and what to use instead for prices/availability. Nothing critical 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 schema description coverage is 100%, with the query parameter already documented as 'Suchbegriff oder Frage'. The tool description does not add semantic detail beyond the schema, so the baseline of 3 applies; no compensation is needed.

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 opens with a specific verb ('Durchsucht') and a concrete resource ('Inhalte des Hotels'), enumerating the content types covered: häufige Fragen, Zimmerkategorien, Pauschalen. It also explicitly names what the tool is not for, distinguishing it from verfuegbarkeit_pruefen without ambiguity.

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 explicit when-to-use guidance by stating that the tool returns hits and that the full text should be retrieved with fetch. It also provides a clear exclusion: 'Für Preise und Verfügbarkeit NICHT geeignet — dafür verfuegbarkeit_pruefen verwenden', directing the agent to the correct sibling tool.

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?

While annotations already mark the tool as read-only, idempotent, and non-destructive, the description adds substantial behavioral context: each offer contains a prefilled booking link, links must be passed unchanged, price does not imply bookability, and the sofort_buchbar/grund fields carry operational meaning. This goes far beyond what annotations reveal.

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 first sentence is an excellent front-loaded summary, and every sentence carries operational value. However, the warning about passing links unchanged appears twice in slightly different forms, adding redundancy to an otherwise focused description.

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, the description covers purpose, live behavior, link handling, price reliability, booking-status semantics, fallback routing to alternative_termine, and guest-facing behavior for non-bookable offers. With an output schema present, return-value details do not need to be repeated.

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 of 3 applies. The description adds some semantic context like 'Endpreise für den gesamten Aufenthalt' and the link/meal-option behavior, but it does not meaningfully elaborate on individual parameters beyond 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 opens with a specific verb and resource: it live-checks which room categories are free for a time period and returns final prices in EUR for the whole stay. This clearly distinguishes the tool from availability-adjacent siblings like alternative_termine and raten_info.

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

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

It gives explicit when-to-use context ('Prüft live'), and explicitly instructs calling alternative_termine when nothing is available. It also provides strong negative guidance: never estimate prices, never reuse older answers, never construct booking URLs yourself.

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 establish read-only, idempotent, open-world safety. The description adds useful behavioral context beyond this by warning that images are large and should be used sparingly, and by indicating that the returned images are meant for direct guest display. 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 sentences, all purposeful: purpose, trigger and source, and usage caution. Information is front-loaded and no words are wasted.

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 read-only media tool with an output schema and full parameter documentation, the description covers purpose, when to call, where the ID comes from, and an important cost/performance warning. Nothing needed for correct invocation is missing.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by stating that zimmertyp_id must come from hotel_info or verfuegbarkeit_pruefen, which helps the agent source the required parameter correctly. This extra context justifies a score above baseline.

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

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

The description states a specific verb and resource: it 'delivers real photos of a room category as images' that are shown directly to the guest. It clearly distinguishes itself from sibling tools that provide descriptions, rates, or availability by focusing on visual appearance and includes concrete trigger phrases ('wie sieht das aus', 'zeig mir').

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

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

It gives explicit when-to-us guidance (when the guest asks about the look of a room) and explicit when-not-to-us guidance (without an explicit request, the textual description suffices). It also tells where the required zimmertyp_id comes from. However, it does not name a specific sibling tool as the preferred alternative, so it falls slightly short of 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?

The annotations already cover read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond that: 'pro_nacht' is automatically multiplied by the number of nights during booking, so the agent should not manually calculate it. This directly prevents a likely misuse.

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, purposeful sentences: the first states the tool's main output, and the second warns about the `pro_nacht` calculation. There is no redundant or filler content.

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 read-only list tool with an output schema, optional language parameter, and clear annotations, the description is complete. It covers what is returned, the booking context, and the one non-obvious behavioral pitfall.

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 already fully documents the single optional `lang` parameter, so the description does not need to repeat it. The baseline of 3 applies because schema_description_coverage is 100% and the description adds no extra parameter-specific 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 what the tool does: it lists additional services that can be booked online, including price and billing type. This is a specific verb and resource, and it distinguishes itself from sibling tools about rates, availability, or hotel information.

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 a clear usage context: use this tool when the agent needs bookable add-on services for an online booking. It does not explicitly name alternatives or exclusions, but the scenario is unambiguous enough to guide selection.

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