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anipotts

imessage-mcp

by anipotts

message_stats

Read-only

Analyze iMessage conversation patterns by generating time-series statistics with flexible grouping options to track messaging trends and activity levels.

Instructions

Aggregate message statistics with flexible time-series grouping. Returns counts, sent/received splits, and averages grouped by day, week, month, year, hour, or day-of-week. By default excludes contacts you've never replied to.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contactNoFilter by contact handle
date_fromNoStart date (ISO)
date_toNoEnd date (ISO)
group_byNoTime grouping (default: month)
include_allNoInclude messages from all contacts, even those you've never replied to (default: false)
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, covering safety and scope. The description adds valuable behavioral context by specifying the default exclusion of contacts never replied to and the types of statistics returned (counts, splits, averages), which are not covered by annotations. No contradiction with 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?

The description is appropriately sized and front-loaded, with two sentences that efficiently convey the tool's functionality and key behavioral trait (default exclusion). Every sentence adds value without redundancy, making it easy to scan and understand.

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?

Given the tool's moderate complexity (5 parameters, no output schema) and rich annotations, the description is mostly complete. It covers the tool's purpose, key behavior, and output types, but could benefit from more explicit usage guidance relative to siblings. The lack of an output schema is partially mitigated by describing return values in the description.

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 fully documents all parameters. The description adds minimal semantic value beyond the schema, such as implying the purpose of 'include_all' with the default exclusion note, but does not provide additional syntax or format details. Baseline 3 is appropriate given high schema coverage.

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's purpose with specific verbs ('aggregate message statistics') and resources ('message statistics'), and distinguishes it from siblings by specifying its unique focus on time-series grouping and exclusion of unreplied contacts. It goes beyond a simple 'get stats' to define the analytical nature of the tool.

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 through its mention of 'flexible time-series grouping' and default exclusions, but does not explicitly state when to use this tool versus alternatives like 'contact_stats' or 'temporal_heatmap'. It provides some context but lacks direct comparisons or exclusions for sibling tools.

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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