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BACH-AI-Tools

Bulk WhatsApp Validator

validate_single_whatsapp_number

Validate a single WhatsApp phone number to check account existence and retrieve metadata like business status and profile information.

Instructions

Enter a single phone number you want to validate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
phoneYesThe whatsapp number must be written as: number (including countrycode); do NOT include any non-number character, spaces, or anything which is not a number. Examples: of correct numbers are: 34123456789 (for spain) or 491234567890 (for Germany).34605797764
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only states what the tool does (validate a number) without disclosing behavioral traits such as what validation entails (e.g., format checks, existence verification), error handling, rate limits, or authentication needs. This is a significant gap for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and efficient, making it easy to understand at a glance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what validation means, what the output might look like (e.g., success/failure, error messages), or any behavioral context. For a tool with no structured data beyond the input schema, this leaves significant gaps in understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the input schema already documents the 'phone' parameter thoroughly with examples and formatting rules. The description doesn't add any additional meaning beyond what's in the schema, but since the schema is comprehensive, a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Enter a single phone number you want to validate.' It specifies the action (validate) and the resource (a single phone number), which is straightforward. However, it doesn't explicitly differentiate from sibling tools like validate_up_to_10, validate_up_to_100, etc., which handle multiple numbers, so it's not a perfect 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for validating a single phone number, but it doesn't provide explicit guidance on when to use this tool versus the sibling tools (e.g., validate_up_to_10 for multiple numbers). It also doesn't mention prerequisites or exclusions, leaving the context somewhat vague.

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

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