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WhatsApp Search Messages

whatsapp_search_messages
Read-only

Offline full-text search across all WhatsApp chats. Only locally-cached messages are searched — no network access required. Optionally restrict search to a specific chat_id. ⚠️ Uses Wacli (unofficial WhatsApp client). Accounts may be restricted for ToS violations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (default 50)
queryYesSearch text (case-insensitive substring match)
chat_idNoOptional chat ID to restrict search

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoPresent only when the search matched nothing, saying so explicitly
countNoNumber of results returned
resultsYesMatching messages

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it searches only locally-cached messages, requires no network access, and warns about Wacli being unofficial with potential ToS violation account restrictions. This goes beyond the annotations and helps the agent understand operational risks.

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?

Three sentences with no waste. The core function is front-loaded, the optional restriction is stated, and the warning is placed at the end. Every sentence earns its place.

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

Completeness4/5

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

The description is complete for a read-only search tool: it covers scope, offline behavior, optional filtering, and a risk warning. The output schema exists, so return values need no explanation. The only minor gap is not explicitly stating how to use chat_id (e.g., where to find it), but the schema and sibling tools like whatsapp_list_chats cover that.

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?

Schema description coverage is 100%, so the schema already documents all three parameters (query, limit, chat_id). The description adds the 'case-insensitive substring match' detail for query and the default of 50 for limit, which are already in the schema. It doesn't add significant new meaning beyond the schema, so baseline 3 is appropriate.

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 clearly states the tool performs offline full-text search across all WhatsApp chats, with an optional chat_id restriction. It distinguishes itself from sibling tools like whatsapp_read_messages and search_messages by specifying the offline/local-cache behavior and the WhatsApp scope.

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?

The description implies when to use this tool: when searching WhatsApp messages offline without network access. It doesn't explicitly name alternatives like whatsapp_read_messages or search_messages, but the offline/local-cache distinction and optional chat_id restriction provide clear context. It lacks explicit exclusions or when-not-to-use guidance.

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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