A sophisticated message history analyzer that extracts relationship dynamics and communication patterns from iMessage and Signal data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install imessage-signal-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install imessage-signal-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is iMessage & Signal Analyzer?
The iMessage & Signal Analyzer is a powerful diagnostic tool designed to provide deep insights into digital communication habits. By interfacing directly with local message databases on macOS and Signal exports on various platforms, this skill allows users to quantify their social interactions. It moves beyond simple text reading to offer a analytical overview of relationship health, tracking how conversations evolve over years through data-driven metrics. This skill is a core component of the Openclaw Skills ecosystem for users seeking to audit their personal or professional communication history.
Whether you are trying to understand a shift in relationship energy or simply need to find historical context within thousands of messages, this tool automates the heavy lifting. It handles the complexities of database querying, binary decoding, and handle aggregation, presenting the user with a conversational summary of their most important interactions.
iMessage & Signal Analyzer Use Cases
- Quantifying relationship dynamics by analyzing who initiates conversations most frequently.
- Identifying historical surges or drops in communication volume to correlate with life events.
- Auditing long-term silence gaps to understand periods of mutual drift or platform changes.
- Reviewing year-by-year tone samples to see how the nature of a relationship has shifted over time.
- Consolidating message history from a single contact across multiple protocols like SMS, iMessage, and RCS.
How iMessage & Signal Analyzer Works
- The skill accesses the local iMessage SQLite database (~/Library/Messages/chat.db) or reads a provided Signal JSON export.
- It identifies and aggregates all handles associated with a specific contact to ensure a complete view of the conversation.
- The analyzer scans message timestamps to detect session breaks, defining a new conversation whenever a gap exceeds four hours.
- It calculates statistical metrics including total message counts, yearly volume distributions, and initiation percentages.
- It extracts representative message samples and recent exchanges to provide qualitative context alongside the quantitative data.
- Finally, it synthesizes these findings into a conversational report within the Openclaw Skills interface, offering interpretations of the relationship energy.
iMessage & Signal Analyzer Setup
For iMessage analysis on macOS, ensure your terminal has Full Disk Access in System Settings -> Privacy & Security.
For Signal analysis, install the signal-cli tool:
brew install signal-cli
signal-cli link
Export your Signal data to a JSON file:
signal-cli export --output ~/signal_export.json
Run the analysis using the following command structure:
python3 skills/message-analyzer/scripts/analyze.py imessage "+15551234567"
iMessage & Signal Analyzer Data Schema & Taxonomy
The skill processes data from various schemas and organizes them into a unified report format:
| Data Point | Source/Method | Description |
|---|---|---|
| Message Volume | SQLite / JSON | Raw count of sent vs. received messages. |
| Initiation Stats | Timestamp Analysis | Tracking who sends the first message after a 4+ hour gap. |
| Silence Gaps | Timestamp Analysis | Flags any periods of inactivity exceeding 30 days. |
| Yearly Samples | Random Sampling | Representative text snippets from each calendar year. |
| Handle Mapping | SQLite Joins | Merges iMessage, SMS, and RCS data for a single contact. |
iMessage & Signal Analyzer Advanced Features
- Intelligent handle aggregation that automatically links different phone numbers and emails for the same contact.
- Partial decoding of macOS attributedBody binary data to recover formatted message content.
- Customizable analysis depth using the --limit flag to control how many messages are processed.
- Cross-platform Signal support allowing for analysis on Linux and Windows systems via JSON exports.
- Automated contact discovery through local AddressBook database integration for easier number lookups.
SKILL.md
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