WhatsApp message templates

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds substantial behavioral context beyond annotations: Meta's ambiguous error message, language sensitivity (en vs en_US), variable count requirements, and the warning against reading count from the preview. Also mentions 0 credits and Meta connection requirement.

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 verbose and uses ALL CAPS for emphasis, which is somewhat heavy-handed. It front-loads the purpose but then spends several sentences explaining why status matters, error messages, and variable counts. While informative, it could be condensed without losing value. The structure is logical but not concise.

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?

With no output schema, the description compensates by explaining key output fields (status, language, variables) and their significance. It also covers prerequisites (Meta connected) and cost (0 credits). It doesn't enumerate all possible output fields, but the essential ones for correct usage are thoroughly addressed.

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 all parameters are already documented. The description's comments about language and variables relate to output fields, not input parameters. It doesn't add new meaning to the input schema, but it reinforces the importance of the status and language filters. 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 clearly states it lists WhatsApp message templates on a Business Account and highlights the review status, which is a key differentiator from siblings like send_whatsapp_message or create_whatsapp_template. The verb 'list' and resource 'WhatsApp message templates' are explicit and unambiguous.

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?

Provides strong contextual guidance: explains when you'd need this tool (before sending, to verify APPROVED status and get exact variable count) and a prerequisite (Meta connected). It doesn't explicitly name alternative tools or say when not to use, but the usage context is clear enough to route an agent correctly.

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