Compare points redemption options for a flight and rank them by cents-per-point (CPP) value. Helps decide whether to pay cash or use loyalty points.
| Name | Required | Description | Default |
|---|---|---|---|
| cashPrice | Yes | Cash price of the ticket in USD | |
| pointsOptions | Yes | Array of available points redemption options to compare |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, so the description does not need to restate safety. It adds useful context about ranking by CPP and the cash-vs-points decision, but does not disclose the exact output format or any edge-case behavior. This is adequate but not rich.
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 compact sentences, front-loaded with the primary action and metric. Every word adds value, and there is no filler or repetition of schema 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 two-parameter calculation tool with read-only annotations, the description is largely complete: it states the inputs' purpose and the ranking behavior. Since there is no output schema, explicitly mentioning the returned format or that higher CPP is better would make it fully complete, but this is easily inferred.
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 schema already documents cashPrice and pointsOptions in full. The description adds conceptual context by linking them to the CPP comparison, but it does not add technical detail beyond what the schema provides. A 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 verb ('Compare', 'rank') and a specific resource ('points redemption options for a flight'), and identifies the key metric (cents-per-point/CPP). It clearly distinguishes this tool from the sibling tools, which deal with predictions, deals, calendars, and flights rather than points optimization.
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 clear context: use this when comparing points redemption options for a flight and deciding whether to pay cash or use loyalty points. It does not explicitly name alternatives or state when not to use the tool, but the context is specific 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.
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Each tool targets a distinct decision point—searching routes, browsing deals, finding flexible dates, predicting fares, and comparing points value. Search_calendar and search_flights are similar, but descriptions clarify date-flexible versus specific-date/route search.
All tool names follow a consistent lowercase snake_case verb_noun pattern: get_prediction, list_deals, optimize_points, search_calendar, search_flights. There is no mixing of conventions or vague verbs.
Five tools is a well-scoped size for a travel deals and points optimization assistant. Each tool earns its place and none feel redundant or unnecessary.
The set covers the core travel decision workflow: searching flights, viewing flexible dates, browsing deals, predicting fare movements, and optimizing points redemption. A fare alert or booking tool is absent, but those are beyond the apparent decision-support scope.
