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test_crm_endpoint

Test connectivity and response of custom CRM endpoints configured in WhatsApp Business stores to verify integration functionality.

Instructions

Probar endpoint CRM — Prueba la conectividad y respuesta de un endpoint CRM personalizado configurado en la tienda [query]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesTipo de endpoint: sidePanel_CustomerInfo, ai_CustomerInitialInfo, sidePanel_CustomerFindToJoin, search_Products, globalSearch
urlYesURL del endpoint a probar
methodNoMetodo HTTP (GET o POST, default GET)
authNoConfiguracion de autenticacion con type (header, basic, body, query) y campos
test_phoneNoTelefono de prueba (default +34600000000)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it states the tool tests 'conectividad y respuesta', it fails to specify whether this invokes actual HTTP requests, whether it's read-only/safe, potential side effects on the target CRM, rate limits, or what response format to expect. For a testing tool with nested auth objects, this lack of safety and behavioral context is a significant gap.

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

Conciseness3/5

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

The description is appropriately brief (single sentence with em-dash separator) and front-loaded with the action. However, the '[query]' placeholder at the end appears to be a template artifact or error, reducing the structural quality and suggesting incomplete metadata.

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

Completeness3/5

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

Given the tool's medium complexity (5 parameters with nested objects) and lack of output schema or annotations, the description meets minimum viability by stating core functionality. However, it omits important context for a testing tool: expected behavior under failure conditions, whether it validates authentication credentials, and the nature of the 'response' being tested.

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 input schema has 100% description coverage, documenting all 5 parameters including the nested auth object structure and default values. The description does not add parameter-specific semantics beyond the schema, but given the high schema coverage, the 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 identifies the tool's function using specific verbs ('Probar', 'Prueba') and resources ('endpoint CRM', 'conectividad y respuesta'). It distinguishes from sibling tools like test_ecommerce_connection and test_email_connection by specifying 'CRM' and 'personalizado configurado en la tienda'. However, the trailing '[query]' artifact suggests possible template residue, slightly reducing clarity.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like update_crm_endpoints (which modifies configuration) or get_crm_health_status (which retrieves health metrics). There are no explicit when-to-use conditions, prerequisites, or exclusions mentioned.

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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