loyalteez_design_program

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

With no annotations, the description carries the full burden of behavioral disclosure. It does add some context by explaining that the AI analyzes the app/community and generates implementation code using documentation context, but it omits critical traits like whether the tool writes to the platform, modifies existing data, requires specific permissions, or is purely generative/read-only.

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 core purpose is front-loaded in the first sentence, followed by a useful second sentence about documentation context. The 'See also' link list is somewhat extraneous but not bloated, and the overall length is reasonable for a complex design tool.

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 tool's complexity, nested input schema, and absence of both annotations and an output schema, the description is adequate but incomplete. It hints at output content ('optimal event structure, tiers, streaks, and implementation code') and provides documentation links, but does not describe the return format or confirm whether the generated program is persisted or merely suggested.

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 all parameters including nested fields like goals, appType, platforms, budget, audience, and existingEvents. The description adds only 'from context' which minimally references the required context parameter, so baseline 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 and resource ('Design a complete loyalty program') and differentiates from siblings like loyalteez_create_event by clarifying that it generates event structure, tiers, streaks, and implementation code rather than executing individual event operations. An agent can immediately tell this is a high-level design/generation tool.

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 no explicit guidance on when to use this tool versus alternatives such as loyalteez_create_event or loyalteez_create_events_batch. It only offers context documentation links ('See also') without stating prerequisites or exclusions, leaving the agent to infer appropriate usage.

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