tool_calculate_points_or_cash

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

No annotations are provided, so the description carries the full burden. It discloses that the tool factors in specific elements and returns a recommendation, but it does not mention whether it accesses external data, modifies any state, or has limitations (e.g., accuracy assumptions). The description gives some behavioral context but lacks completeness for a fully transparent disclosure.

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 a concise introductory sentence and a clearly formatted Args block. It is front-loaded with the decision question. The Args block is somewhat lengthy but necessary given the lack of schema descriptions. No superfluous sentences.

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 7 parameters, 0% schema coverage, no output schema, and no annotations, the description covers the essential purpose and parameter semantics well. It lacks details about the output format (the 'recommendation') and potential error cases, but for a calculation tool, this is acceptable. The description is largely complete for effective use.

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 0%, but the description compensates fully by providing detailed parameter explanations in the Args block. Each parameter is explained with its role, examples (e.g., programs, categories), and context (e.g., 'taxes_fees_on_award' default 0). This adds significant meaning beyond the bare type information 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 clearly states that the tool decides between cash and points for a booking, and returns a recommendation. The verb 'calculate' and the specific resource 'points_or_cash' make the purpose unambiguous. It is distinct from sibling tools like estimate_points_value or compare_points_programs, which do not directly compare cash vs points for a given booking.

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 implies usage for making a cash-vs-points decision by listing factors considered (cpp, opportunity cost, points-back earning). It does not explicitly state when not to use it or suggest alternatives, but the context is clear given the tool's purpose.

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