wafle_ai_support_hint

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

With no annotations, the description carries the full burden. It discloses key behavioral traits (PII redaction and LLM usage), but does not specify side effects, permissions, or whether it modifies any data. This leaves some ambiguity about safety and consequences.

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 two sentences, front-loaded with the main purpose and followed by a relevant privacy detail. Every word earns its place, with no unnecessary filler.

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?

There is no output schema, so the description should explain the return value. It implies a drafted response but doesn't explicitly state the output format. The optional parameters are not explained, which is a notable gap for a tool with 5 parameters.

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 only 20% (only slug has a description). The description clarifies that inbound_message is the message to process and mentions redaction of emails/phones, but parameters like total_orders and last_orders_summary remain unexplained, leaving the agent without sufficient guidance.

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 the tool's function as a customer-service co-pilot with specific verbs: classify, gauge sentiment, decide escalation, and draft a response. It identifies the resource (inbound message) and distinguishes from sibling AI tools like wafle_ai_categorize and wafle_ai_product_describe.

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 provides clear context for when to use the tool—for customer-service inbound messages—but does not explicitly mention alternatives or when not to use it. The implied usage is strong enough for most cases.

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