OpenClaw Skill Connects Agents to Knods.io UI for Workflow Creation
A developer has created an OpenClaw skill that connects AI agents directly to the Knods.io user interface for asset creation workflows.
Current Capabilities
The skill enables OpenClaw agents to:
- Understand the Knods.io UI structure and functionality
- Create workflows within the Knods platform
- Switch between specific agents instead of using Knods' built-in agent
As demonstrated in the source, users can employ brand-specific agents within the Knods interface. A video demonstration shows the skill in action: https://youtu.be/hRZeK0jo9OI?si=-C-b4PyRVxDWPGlS.
Technical Details
The skill was developed using:
- GPT-5.3 Codex for the skill implementation
- GPT-5.4 for the agent shown in the demonstration
The developer notes the irony of using GPT models despite being "mostly an Opus fan."
Future Development
Planned next steps include:
- Creating a headless bridge to enable agent operation from multiple platforms including Telegram, WhatsApp, and TUI (terminal user interface)
- Integrating with other skills like Meta Ads for campaign automation
- Enabling full campaign automation via Telegram
The skill is currently available on ClawHub as a work in progress.
📖 Read the full source: r/openclaw
👀 See Also
md-viewer: A Live-Reloading Markdown Viewer for Claude Code Workflows
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HomeButler: Zero-token homelab management for OpenClaw agents
HomeButler is a single Go binary that lets OpenClaw agents manage homelab infrastructure without API keys or tokens. It runs locally and keeps all operations on your network.
Black LLAB: Open-Source Architecture for Dynamic Model Routing and Docker-Sandboxed AI Agents
A developer has open-sourced Black LLAB, a system that uses Mistral 3B to route prompts between local and cloud models and runs AI agents in isolated Docker containers with OpenClaw integration.
Conduid: Trust Infrastructure Layer for MCP Servers Built with Claude
Conduid indexes over 25,000 MCP servers across GitHub, npm, PyPI, and major directories, scoring each 0-100 based on GitHub activity, security posture, documentation quality, and maintenance signals. The entire codebase was written with Claude by a solo founder.