claw-canvas_skill

Overview

This skill provides a virtual canvas that OpenClaw can use to output content and visualize its internal thinking during development. It creates an interactive surface for formatted text, images, charts, and progress updates. The canvas improves transparency and speeds debugging by making intermediate results easy to inspect and share.

How this skill works

The skill wraps the agent's native canvas tool and exposes a simple CLI for rendering Markdown, HTML, images, and data visualizations. Agents push updates to the canvas to show thought steps, decision trees, or real-time task progress. Snapshots can be saved to capture the canvas state for review or archival purposes.

When to use it

• When you want the agent to show step-by-step reasoning or decision traces.
• To preview drafts of content (blog posts, tweets, documentation) with formatting.
• During data analysis to display charts, tables, and intermediate results.
• While debugging complex flows to visualize program state or architecture diagrams.
• To create shareable snapshots of agent outputs for demos or reviews.

Best practices

• Keep each canvas frame focused on a single topic or task for clarity.
• Use Markdown/HTML for structured content and images for visual data to maximize readability.
• Update the canvas incrementally to reflect progress rather than dumping large outputs at once.
• Annotate snapshots with timestamps and short notes to preserve context.
• Limit interactive thinking displays to essential steps to avoid exposing irrelevent internal noise.

Example use cases

• Display an agent's stepwise reasoning when exploring a multi-step coding task.
• Render draft blog posts or social content with formatting for quick review and edits.
• Visualize data analysis results with charts and tables while iterating on transformations.
• Show architecture diagrams or program flow during design discussions.
• Capture snapshots of the canvas to archive versions of agent outputs for later comparison.