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austindixson

Claw Canvas

by austindixson · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
514
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Install in OpenClaw
/install claw-canvas
Description
A virtual canvas for OpenClaw to output content and visualize its thinking during development.
README (SKILL.md)

Claw Canvas Skill

Description

This skill wraps OpenClaw's native canvas tool to provide a dedicated, interactive surface for the agent to visualize its internal processes, display intermediate results, and output rich content directly on a virtual canvas. It enables a more transparent and intuitive development workflow by making the agent's thinking and work-in-progress visible.

Core Functionalities

  • Render Markdown/HTML: Display formatted text, code, tables, and images.
  • Visualize Data: Present charts, graphs, or structured data.
  • Show Progress: Update the canvas with real-time progress of tasks.
  • Interactive Thinking: Optionally display thought processes or decision trees.
  • Snapshot: Capture the current state of the canvas.

Usage

This is primarily an internal skill for the agent to use to illustrate its workflow. It will expose a CLI interface for displaying content.

# Example: Display markdown content
python3 scripts/canvas_cli.py display_markdown --content "# Agent Thinking\
\
Here's my current thought process..."

# Example: Display an image
python3 scripts/canvas_cli.py display_image --url "https://example.com/image.png"

Purpose

To enhance transparency, improve user understanding of complex agent processes, and provide a dynamic, real-time output area for development tasks. This will be invaluable for tasks like:

  • Visualizing website structure during the Mac App conversion.
  • Displaying drafted blog posts or tweets with formatting.
  • Showing data analysis results.
  • Illustrating program flow or architectural decisions.
Usage Guidance
This appears to be a small, legitimate helper that forwards content to the agent's canvas API. Before installing: (1) verify what openclaw.default_api.canvas does in your runtime (does it store, forward, or expose canvas contents externally?), (2) note that the SKILL.md advertises image/progress features that the included script does not implement — if you need those, request or inspect an updated implementation, (3) test the CLI in a safe environment to confirm behavior and output destinations, and (4) if you are concerned about sensitive content being shown, avoid sending secrets to the canvas and confirm any viewers/servers that can access canvas contents.
Capability Analysis
Type: OpenClaw Skill Name: claw-canvas Version: 1.0.0 The `scripts/canvas_cli.py` skill takes arbitrary string input via the `--content` argument and passes it directly to the `default_api.canvas` tool for rendering. As the `SKILL.md` indicates the canvas can 'Render Markdown/HTML', this direct passing of unsanitized user-controlled content creates a potential vulnerability (e.g., Cross-Site Scripting if HTML is rendered, or other forms of injection) if the underlying `canvas` tool does not robustly sanitize or sandbox the input. This lack of input sanitization is a risky capability, classifying the skill as suspicious rather than benign, but not malicious as there's no evidence of intentional harmful behavior by the skill itself.
Capability Assessment
ℹ Purpose & Capability
The name/description match the code: the CLI sends markdown to openclaw.default_api.canvas to present content. However SKILL.md advertises additional features (display_image, progress, snapshot, interactive thinking) that are not implemented in scripts/canvas_cli.py (only display_markdown exists). This is an inconsistency but not evidence of malicious behavior.
ℹ Instruction Scope
Runtime instructions are narrowly scoped to invoking the CLI to display content. The SKILL.md examples include an image-display command that the included CLI does not implement; otherwise the instructions do not request files, credentials, or unrelated system data. The CLI calls default_api.canvas — review what that API does in your runtime because the script delegates output handling to it.
✓ Install Mechanism
No install spec and only a small Python script are included. Nothing is downloaded or written during install by this package itself.
✓ Credentials
No environment variables, credentials, or config paths are required. The only dependency is the presence of an openclaw.default_api object at runtime (expected for an OpenClaw skill).
✓ Persistence & Privilege
The skill does not request always:true, does not modify other skills or global configuration, and has no install-time persistence instructions.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install claw-canvas
  3. After installation, invoke the skill by name or use /claw-canvas
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of Claw Canvas, providing a virtual, interactive surface for agent visualization: - Offers rendering of Markdown/HTML, images, charts, and tables. - Displays agent's thinking and progress in real-time. - Includes a CLI for displaying various content types on the canvas. - Supports capturing canvas snapshots. - Aims to enhance workflow transparency and output visualization during development.
Metadata
Slug claw-canvas
Version 1.0.0
License —
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Claw Canvas?

A virtual canvas for OpenClaw to output content and visualize its thinking during development. It is an AI Agent Skill for Claude Code / OpenClaw, with 514 downloads so far.

How do I install Claw Canvas?

Run "/install claw-canvas" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Claw Canvas free?

Yes, Claw Canvas is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Claw Canvas support?

Claw Canvas is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Claw Canvas?

It is built and maintained by austindixson (@austindixson); the current version is v1.0.0.

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