generate_reengagement_message

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

No annotations exist, so the description must carry behavioral weight. It states the output includes three components but does not disclose how the message is generated (e.g., AI model usage) or any constraints like token limits or personalization depth.

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 sentences efficiently convey the tool's purpose, outputs, and usage context. Every word adds value, with no redundancy.

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 existence of a separate output schema, the description adequately notes the return types. It covers the core intent and expected outputs, though it could mention the generation methodology or rate limits for completeness.

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 coverage is 100%, so the input schema already details all parameters. The description adds 'personalized' as context but does not enhance meaning beyond schema descriptions. Baseline 3 applies.

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 explicitly states the tool generates a personalized re-engagement message for an inactive student, listing specific outputs (subject line, email body, WhatsApp-friendly short message). This clearly differentiates it from siblings like 'analyze_course_feedback' or 'triage_support_query' which serve different purposes.

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 includes 'Use for growth team automation,' indicating appropriate context. However, it does not explicitly state when not to use or mention alternatives among siblings, leaving some ambiguity.

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