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A virtual canvas for OpenClaw to output content and visualize its thinking during development.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Seamless bidirectional bridge between nanobot (Ollama Mistral orchestrator) and overstory (Claude Code agent swarm). Routes tasks through the OverClaw gateway (port 18800) to overstory for subagent coordination, syncs memory.
Integrates OpenClaw with the FunClip AI video editor to enable AI-powered video recognition and clipping via command line.
IMPORTANT: OpenRouter is required. Routes tasks to the right model and always delegates work through sessions_spawn. Rejects prompt-injection patterns in task strings (v1.7.6+).
Automatically create clips and videos from media files in a specified folder. Uses Agent Swarm for intelligent task delegation and supports cron-based scheduling.
Analyzes journal entries and chat history to identify high-value topics and automatically generate blog posts.
Extracts and analyzes Cursor IDE chat history to identify key discoveries, obstacles, and solutions, saving findings to the journal.
| name | claw-canvas |
| displayName | Claw Canvas |
| description | A virtual canvas for OpenClaw to output content and visualize its thinking during development. |
| version | 0.1.0 |
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.
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\n\nHere's my current thought process..."
# Example: Display an image
python3 scripts/canvas_cli.py display_image --url "https://example.com/image.png"
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: