A specialized skill for formatting AI agent outputs into mobile-optimized, Unicode-based visual reports for chat platforms.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install scannable-reports
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 scannable-reports 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 Scannable Reports?
Scannable Reports is an essential utility within the Openclaw Skills ecosystem designed to solve the problem of data visualization in plain-text environments. While most chat applications like Telegram, Discord, and Slack do not support complex embedded charts or HTML, this skill leverages standard Unicode characters to create professional-grade visual data representations. It allows developers to generate progress bars, trend sparklines, and status indicators that render perfectly across mobile and desktop clients without the overhead of image generation.
By prioritizing a mobile-first approach, this skill ensures that technical updates and metrics are immediately digestible for users on the go. It synthesizes complex agent data into a signal-heavy format, utilizing monospace alignment and specific emoji taxonomies to provide high-density information in a small screen footprint.
Scannable Reports Use Cases
- Delivering automated daily project status updates directly to team Slack or Discord channels.
- Monitoring system health and server resources with real-time Unicode progress bars via Telegram.
- Reporting financial performance and revenue trends using sparklines for quick visual analysis in WhatsApp.
- Creating scannable, high-priority alerts that use status emojis to signify urgency and required action.
- Transforming raw data logs into clean, monospace tables for better readability in mobile-first environments.
How Scannable Reports Works
- The AI agent detects a trigger for a status report, dashboard update, or metrics summary.
- The skill processes numerical input and applies a 10-character bar formula using Unicode blocks (โ and โ) to visualize percentage completion.
- Historical data points are mapped to a specific vertical character set (โ to โ) to generate sparklines representing trends or momentum.
- Status indicators are assigned based on the severity or state of the data using a standardized emoji mapping (e.g., ๐ด for critical, ๐ข for healthy).
- The output is structured with a "Lead with Signal" hierarchy, ensuring the most critical information appears at the top of the chat bubble.
- Where supported, the content is wrapped in monospace formatting to ensure precise alignment of tables and visual elements.
Scannable Reports Setup
To add this capability to your agent, install it via the CLI using the following command:
openclaw install scannable-reports
Once installed, you can prompt your agent to apply these formatting patterns to any data-heavy output intended for mobile consumption.
Scannable Reports Data Schema & Taxonomy
The skill organizes its output using a standardized visual taxonomy to ensure consistent rendering across different Openclaw Skills implementations.
| Element Type | Unicode / Emoji Used | Purpose |
|---|---|---|
| Progress Bar | โ, โ, โ, โ |
Visualizes completion percentages |
| Sparklines | โ, โ, โ, โ
, โ, โ, โ |
Represents data trends over time |
| Status Emojis | ๐ข, ๐ก, ๐ด, ๐ฅ, โก | Indicates health, warnings, or urgency |
| Dividers | โโโ |
Separates logical sections within the report |
| Tables | Triple Backticks (```) | Ensures column alignment in monospace-supported apps |
Scannable Reports Advanced Features
- Multi-platform compatibility logic that adjusts formatting for restricted environments like WhatsApp or iMessage.
- Trend-aware momentum analysis that automatically generates sparklines based on provided historical arrays.
- Monospace table generation for structured data presentation in mobile chat windows.
- Signal-first information hierarchy that extracts the most relevant status updates for the top of the message.
SKILL.md
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