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WhatsApp: List conversations

whatsapp_list_conversations
Read-onlyIdempotent

List WhatsApp chats from the user's own connected WhatsApp account. Use to find a chat_id before reading or sending when the user identifies a conversation by person/name rather than ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
account_idNoOptional Nilyo connection ID (unipile_account_id from list_connected_accounts). Omit when the user has one account for this provider. When several exist, Nilyo never guesses: list them (display name, identifier, provider user ID), choose the one the user named or ask, and pass its ID here.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful scoping context ('from the user's own connected WhatsApp account') and workflow context, but does not disclose output shape, pagination behavior, or how results are ordered—minor gaps given the rich annotations.

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?

Two short sentences, both purposeful: the first identifies the action and scope, the second explains when to use it. No filler or redundant restating of the tool name.

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?

The description provides the core purpose and use case, but with no output schema it should state more about what the returned conversations look like and whether limit controls the number of returned chats. It is adequate for a simple list tool, but leaves room for ambiguity around return values and edge cases.

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

Parameters2/5

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

Schema description coverage is only 50%: account_id is well documented in the schema, but limit has only a name and bounds, and the tool description adds no parameter-level meaning. Because the description does not compensate for the undocumented limit parameter, parameter semantics are only partially conveyed.

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

Purpose5/5

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

The description states a specific verb and resource: 'List WhatsApp chats from the user's own connected WhatsApp account.' It also clarifies the operational purpose—finding a chat_id before reading or sending—which distinguishes it from read/send and other provider-specific conversation-listing tools.

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

Usage Guidelines4/5

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

It explicitly says to use this when the user identifies a conversation by person/name rather than ID, which is a clear triggering condition. It implies the alternative path (reading/sending after obtaining a chat_id) but does not name alternative sibling tools such as whatsapp_read_conversation or messaging_list_chats.

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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