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

The annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds important behavioral context: it mandates that the LLM 'MUST infer the user language from the conversation and pass it via the locale parameter' and explains that UI text and responses are localized. It also discloses that results deep-link to Tripuck.com for booking. No contradictions.

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, leading with the core purpose, then usage examples, input format, and language/currency behavior. Every sentence adds value, and the length is appropriate for a tool with 10 parameters. It is front-loaded with the most important information.

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 without an output schema, the description covers the essential context: what it does, when to use it, required input formats, and how locale/currency defaults work. It also gives a hint about the response (deep-linking to Tripuck.com for review/booking). However, it doesn't describe the structure of the fare results, which would be helpful for an agent to set expectations.

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 input schema already covers all 10 parameters with 100% coverage, including descriptions for IATA codes, date formats, locale, and currency defaults. The description reiterates these conventions (e.g., 'Inputs: IATA codes (IST, AYT, LHR...) and dates in YYYY-MM-DD') but doesn't add new semantic meaning beyond what the schema provides. It does emphasize the mandatory inference of locale, but that's already 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 opens with 'Tripuck flight meta-search — real-time fare comparison across 700+ airlines and 50+ online travel agencies,' which clearly states the tool's function (searching/comparing flight prices) and scope. It also provides concrete query examples ('Istanbul to Antalya tomorrow') and input conventions, distinguishing it from siblings like flight_details (which handles specific flight details) even though it doesn't explicitly name alternatives.

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 'Use this tool when the user asks for flight prices' and lists multilingual examples, making the trigger conditions clear. However, it does not mention when not to use it or reference alternatives like cheapest_dates or flight_details, so it lacks exclusions.

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