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Locate iMessage messages by their text content. Filter results by conversation and date to find specific messages in your macOS history.

Instructions

Search decoded message bodies for a substring (case insensitive).

Optionally restrict to one chat (same matching rules as read_thread) and to messages on or after since ("YYYY-MM-DD" or "YYYY-MM-DD HH:MM").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chatNo
textYes
limitNo
sinceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral burden. It discloses meaningful behavior: search targets decoded bodies, matching is case-insensitive, and the since parameter accepts specific date/time formats. It does not explicitly state read-only status or pagination behavior, but 'search' implies non-mutating and the output schema covers return shape.

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 compact and front-loaded with the core action. The second sentence adds only useful optional-filter details, with no filler or repetition of schema information.

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

Completeness5/5

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

For a 4-parameter tool with an output schema, the description covers the required text parameter and the non-trivial optional filters, including accepted date formats. The one unmentioned parameter, limit, is adequately defined in the schema with its name and default, so an agent has enough information to invoke the tool correctly.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It adds real semantics for text (case-insensitive substring), chat (optional restriction with matching rules aligned to read_thread), and since (on-or-after with two accepted formats). The limit parameter is not mentioned, but its schema title and default value of 50 make it self-explanatory.

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 opens with a specific verb and resource: 'Search decoded message bodies for a substring (case insensitive).' It also references read_thread for chat matching rules, which helps differentiate this tool from sibling tools like list_chats and read_thread.

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 the main use case—locating messages by substring—and explains optional chat and since filters. However, it does not explicitly state when to prefer search over read_thread or list_chats, nor does it provide exclusions. The 'same matching rules as read_thread' note is about parameter behavior, not tool selection.

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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