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

Annotations cover readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description goes beyond these by disclosing that prices may shift, that it never collects payment details, that it returns a click-through link, and that expired offers produce a specific error message. This provides rich behavioral context that annotations alone do not offer, and 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 well-structured with clear sections (main description, Args, Returns, Examples, Error Handling) and is front-loaded with the core purpose. It is somewhat repetitive of the input schema (the Args section duplicates schema descriptions), but each section carries useful information and there is no fluff. A slightly tighter version could omit the repetition, but overall it is appropriately concise 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?

With no output schema, the description compensates by listing the exact fields returned (hotel name, price, dates, room, board, cancellation deadline, booking link). It also covers error handling and usage context. For a single-offer detail tool with read-only semantics, nothing essential is missing for an agent to call 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?

Schema coverage is 100%, so the schema already fully documents both offer_id and response_format, including their types, defaults, and descriptions. The description repeats the same info (e.g., 'offerId returned by search_flexible_hotel_offers') without adding new meaning beyond what the schema provides. The expiry note appears in error handling, not in parameter semantics, so the description adds marginal value over 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 states a specific verb ('fetch'), a precise resource ('full, up-to-date details for a single hotel offer previously returned by search_flexible_hotel_offers'), and explicitly ties it to a sibling search tool. This clearly differentiates it from the siblings (resolve_city_code, list_hotels_in_city, search_flexible_offers), so an agent knows exactly what this tool does and when to use it.

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 'Use when' and 'Don't use when' examples, including a concrete scenario (double-check price before booking) and a negative condition (no offer_id yet -> run search first). It also states the timing requirement ('call this before telling the user a final price or sending them to book'), leaving no ambiguity about when to invoke this 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?

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds genuine value beyond annotations: it discloses that the tool does NOT return prices/availability, states 'This tool does not modify any data' (consistent with destructiveHint=false), and documents the exact error message for invalid city codes. There is 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?

The description is organized with clear section headers (Args, Returns, Examples, Error Handling) and is front-loaded with the core purpose. Every section earns its place — the examples, error handling, and return description all add operational value. Slightly longer than minimal, but the structure makes it scannable, and no sentence is 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?

The tool is simple (4 params, 1 required, all schema-documented, no nested objects, no output schema) with rich annotations. The description covers what's returned (hotel name, hotelId, chain code, coordinates), error handling, the chaining pattern with search_flexible_hotel_offers, and when not to use it. An agent has everything needed to call it correctly — including awareness that no output schema exists but the return content is described.

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 baseline is 3. The description largely mirrors the schema (e.g., radius range 1-300, default 20, response_format enum). It adds modest value by embedding usage context in the examples (e.g., 'narrow radius_km' for a beachfront search, 'use resolve_city_code to find it' — though that hint also exists in the schema). The description doesn't introduce meaning beyond what the schema provides, so 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 precise verb-resource-scope combination: 'List hotels (with their Amadeus hotelId) located in a given IATA city code, optionally within a radius.' It explicitly differentiates itself from search_flexible_hotel_offers by clarifying it returns only hotel identity/location, NOT prices or availability. An agent can distinguish this from all three siblings without opening their schemas.

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 names the exact alternative (search_flexible_hotel_offers), the chaining pattern (pass returned hotelIds into it), and provides concrete 'Use when' / 'Don't use when' examples. It even shows how to narrow radius_km for neighborhood-specific searches. Nothing about when to invoke this tool 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds beyond these by specifying the return format (name, iataCode, country code), the exact error message ('No cities found matching ...'), and clarifies it is a pure lookup with no side effects. 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?

The description is well-structured and front-loaded with purpose and usage context. It includes a clear one-liner, a brief explanation of why it's used first, parameter descriptions (somewhat redundant with schema), returns, examples, and error handling. It is slightly lengthy due to repeating the Args section, but every section earns its place and the structure aids comprehension.

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 lookup tool with three parameters, no output schema, and strong annotation coverage, this description covers all necessary aspects: purpose, when to use, examples, return format, and error handling. An agent can invoke it correctly without ambiguity, making it 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 description coverage is 100% with all three parameters fully documented. The tool description repeats parameter details (e.g., max_results range and default, response_format enum) but adds no new semantic meaning beyond what the schema already provides. It reinforces usage examples but does not introduce additional information, so the baseline of 3 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 states a specific action and resource: 'Look up the 3-letter IATA city code for a free-text city name,' with concrete examples (Tel Aviv -> TLV, Paris -> PAR). It clearly distinguishes itself from sibling tools by explaining that all other tools require an IATA city_code, making this the prerequisite lookup tool.

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 states when to use it ('normally the first tool to call when the user names a city') and when not to use it ('Don't use when: you already have a 3-letter IATA city code'). It names dependent tools (list_hotels_in_city, search_flexible_hotel_offers) and provides a concrete example of usage 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?

While annotations already declare readOnlyHint and destructiveHint=false, the description enriches the behavioral profile substantially. It discloses an affiliate-search model ('never collects payment details or creates a booking'), the external bookingUrl flow, the Amadeus sandbox data source, per-date error handling via datesSkipped, and the scanning of every check-in date. These details go well beyond the annotations and materially shape an agent's expectations for side effects and response quirks. No contradiction with annotations; readOnlyHint aligns with the stated no-booking 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 long but unusually well-organized. It front-loads the core concept and the key differentiator (flexible window vs fixed dates) in the opening sentences, then flows logically through an example, non-use cases, affiliate disclaimer, parameter list, return shape, usage examples, and error handling. Every section earns its place: the return JSON is especially valuable given the lack of an output schema, and the error-handling note covers edge cases an agent would otherwise discover only at runtime. No redundant filler; the length is justified by 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 an 11-parameter tool with no output schema, the description is exceptionally complete. It specifies the exact JSON return structure, including datesSkipped with reason fields and the cheapest summary object, which an agent needs to parse results reliably. It covers error conditions (window >30 days, per-date failures), explains the scanning algorithm, and provides two representative use cases. Combined with full schema parameter descriptions and annotations, nothing required to correctly invoke and interpret this tool 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 each parameter is already documented. The description adds value by explaining the conceptual relationship between earliest_check_in and latest_check_in as a 'window' with a worked example ('3 nights in Tel Aviv... is expressed as nights=3, earliest_check_in="2026-09-01", latest_check_in="2026-09-20"'), and by clarifying default behaviors (max_hotels auto-check, response_format selection). These additions go beyond simple schema repetition, though the marginal gain is modest since the schema descriptions already cover the same facts. A solid 4, not a 5 because the added insight is illustrative rather than essential.

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 precise statement: 'Find the cheapest hotel offers for a fixed NUMBER OF NIGHTS across a WINDOW of possible check-in dates.' It specifies the resource (hotel offers), the action (find cheapest), and the distinctive scope (flexible dates rather than fixed). It also explicitly positions itself as 'the core tool of this server' and contrasts with sibling tools such as list_hotels_in_city and resolve_city_code, making its role unmistakable. No 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?

Usage guidance is explicit and actionable. It provides concrete when-to-use examples ('find me the cheapest 3-night stay in Paris sometime in the next month') and a clear don't-use case ('Don't use when: the user already has exact fixed dates in mind'), followed by the recommended alternative (set earliest_check_in = latest_check_in). It also points to companion tools (resolve_city_code, list_hotels_in_city) for prerequisites, making routing between siblings trivial.

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