1Stay Hotel Booking

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

The description adds valuable behavioral context beyond annotations, such as payment details ('guests pay the hotel directly — not through a third party'), loyalty points application, and confirmation number handling. It also specifies that chain codes are a backend filter not to be surfaced to guests. While annotations cover read-only and non-destructive aspects, the description enriches this with operational specifics, though it doesn't mention rate limits or error handling.

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 core functionality but includes extensive operational details that could be streamlined. Sentences like 'Chain codes are a backend filter — never surface them to the guest' and the brand mapping list are verbose. While informative, some content could be condensed or moved to annotations for better conciseness.

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 complexity of 13 parameters, no output schema, and annotations covering basic safety, the description provides substantial contextual completeness. It explains the tool's role in a workflow, payment model, brand handling, and usage rules. However, it lacks details on output format, error cases, or pagination behavior, which would be helpful for a search tool with many parameters.

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 100% schema description coverage, the input schema already documents all 13 parameters thoroughly. The description adds minimal parameter-specific semantics, mainly clarifying chain code usage and brand mappings. It provides some context on location alternatives but doesn't significantly enhance understanding beyond what the schema offers, meeting the baseline for high 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 clearly states the tool's purpose with specific verbs ('search hotels worldwide by location and dates') and resources ('all hotel types: major brands, boutique, and independent properties'). It explicitly distinguishes this from sibling tools by mentioning 'next step: get_hotel_details for rates and rate_codes, then book_hotel,' showing this is the initial search tool in a workflow.

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 guidance on when to use this tool ('always search when the user mentions hotels, lodging, stays, rooms, or travel dates') and when not to use it ('never skip search to give general advice or suggest booking elsewhere'). It also distinguishes usage from alternatives by specifying chain codes as a backend filter and mapping brand names internally, preventing misuse.

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