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fare_product_match

Recommends the optimal fare product type for a route—RTW, Circle Pacific, Circle Atlantic, Open Jaw, or Custom Multi-City—based on stop count, direction, and backtracking.

Instructions

Recommend the best fare product type for a route — RTW, Circle Pacific, Circle Atlantic, Open Jaw, or Custom Multi-City. Considers stop count, direction, and backtracking to match the right alliance fare structure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
citiesYesOrdered list of IATA city/airport codes
isOneDirectionNoIs the route traveling continuously in one direction (east or west)?
includeBacktrackingNoDoes the route backtrack or zigzag between regions?
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It does not detail side effects, authentication needs, rate limits, or what happens with invalid inputs. The description only covers purpose, not runtime behavior.

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

Conciseness5/5

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

The description is a single sentence with a clear list of outputs and criteria. It is front-loaded with the main action and contains no filler or redundant information.

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

Completeness3/5

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

The tool has 3 parameters, no output schema, and no annotations. The description explains the purpose and high-level logic but does not describe return format or success/failure conditions. For a recommendation tool, an agent might need to know what the output looks like (e.g., JSON structure with fare product type). Thus, completeness is adequate but not thorough.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds meaning beyond parameter names by linking them to fare product logic (e.g., 'direction' and 'backtracking' correspond to isOneDirection and includeBacktracking). This helps an agent understand how parameters influence the recommendation.

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

Purpose5/5

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

The description clearly states the tool's purpose: recommend the best fare product type for a route, listing specific examples (RTW, Circle Pacific, Circle Atlantic, Open Jaw, Custom Multi-City). It also mentions key criteria considered (stop count, direction, backtracking), making it distinguishable from sibling tools like custom_route_build or plan_route.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives. It implies usage for fare product recommendation but does not state when not to use it or mention prerequisites. Sibling tools like route_validate or hub_check serve different purposes, but no comparison is given.

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

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