ask_user_via_whatsapp

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

With no annotations provided, the description carries full burden and does well by explaining key behavioral traits: it's a blocking operation that waits for user replies, has timeout and polling mechanisms, and enables autonomous continuation. It doesn't cover error handling or rate limits, but provides substantial operational context beyond basic functionality.

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 well-structured with clear sections (WHEN TO USE, DO NOT, HOW IT WORKS, EXAMPLE USAGE, USER EXPERIENCE) and uses bold formatting effectively. While slightly verbose at 14 sentences, every section adds value and the information is front-loaded with the most critical guidance first.

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?

For a complex tool with 5 parameters, no annotations, and no output schema, the description provides substantial context about behavior, usage scenarios, and workflow. It explains the blocking nature and user experience well. The main gap is lack of output format details, but overall it's quite complete for enabling effective tool use.

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 5 parameters thoroughly. The description's example usage shows parameter application but doesn't add significant meaning beyond what the schema provides. Baseline 3 is appropriate when 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 explicitly states the tool's purpose: to send questions to users via WhatsApp and wait for replies, enabling AI assistants to continue working autonomously. It clearly distinguishes this from sibling tools (all WhatsApp-related operations) by focusing on user interaction for unblocking progress, not messaging functions like waha_send_text.

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 explicit guidance with 'WHEN TO USE' and 'DO NOT' sections, listing specific scenarios (architectural decisions, missing requirements, API keys, etc.) and alternatives to avoid (stopping work, manual input). It clearly defines when this tool should be used versus other approaches.

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