put_loyalties

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

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond annotations, including 'Immediate effect - Changes apply to new bookings right away' and the return information in 'What You Get.' It does not cover permissions or error behavior, but the annotations lower the bar.

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 markdown structure is front-loaded with an Overview and useful sections, but the content is repetitive for a simple two-parameter tool. Enable/disable and cashback rate concepts are repeated across 'When to Use,' 'Key Features,' and 'Quick Start,' reducing conciseness. It is adequately structured but not tight.

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 low complexity, 100% schema coverage, rich annotations, and no output schema, the description is mostly complete. It explains parameters, required fields, immediate effect, and expected confirmation/status results. It omits permission or error context, but the definition is sufficient for correct invocation.

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%, and both parameters are documented in the schema with enum and example details. The description repeats the same required fields and examples ('status' as 'enabled' or 'disabled', 'cashbackRate' as decimal e.g. 0.1 for 10%) without adding constraints or syntax beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 a specific verb and resource: 'Configure your loyalty program settings, including enabling/disabling the program and setting cashback rates.' This distinguishes the tool from read-oriented siblings like get_loyalties, though it does not explicitly name an alternative or contrast with them. The purpose is clear and actionable.

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 'When to Use' section provides clear contexts: program activation, rate adjustments, program management, and A/B testing. It does not state when not to use the tool or name alternative siblings, but it gives sufficient positive guidance for an agent to select it correctly.

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