canonry

What This Skill Does

Canonry is a powerful, open-source command-line interface (CLI) tool designed for Answer Engine Optimization (AEO). In an era where AI-driven search engines like ChatGPT, Gemini, Claude, and Perplexity are becoming primary sources of traffic, Canonry allows developers and marketers to monitor how their domain is cited. The tool systematically queries these AI engines against specific target keywords to track whether your site is being surfaced, omitted, or cited in the generated responses. By providing structured evidence and analytics, it turns the opaque world of LLM-based search into actionable data.

Installation

To integrate Canonry with OpenClaw, use the provided install command: clawhub install openclaw/skills/skills/arberx/canonry. Ensure you have Node.js installed on your system. Once the skill is installed, run canonry init to provide your API keys for Gemini, OpenAI, and Claude. Before executing any sweeps, verify that the daemon is active by running canonry start.

Use Cases

Use Canonry to perform competitive intelligence by identifying which domains rank for your target queries. It is essential for content strategists measuring the ROI of SEO efforts in AI-centric search. If you have recently optimized your landing pages for better AI retrieval, use this skill to validate those changes over time. Additionally, use it to troubleshoot why your site might be losing visibility in specific models versus others, allowing for more targeted adjustments to your site's schema and content structure.

Example Prompts

1. "OpenClaw, please use the canonry skill to set up a new project for our site example.com and add the keyword 'best productivity software' to the tracking list."
2. "I need to analyze our search performance. Can you trigger a visibility sweep using the canonry skill for the current project? I've confirmed I have enough API quota for the requests."
3. "Summarize the latest evidence from the canonry sweep. Which of the AI models are currently failing to cite our domain for the primary keyword 'how to build widgets'?"

Tips & Limitations

• Quota Awareness: Sweeps consume significant API credits. Always check your provider usage logs and confirm with the user before triggering large-scale runs.
• Observability Lag: Canonry is an observability tool; it will not show real-time changes. AI models have training cutoffs and indexing delays, so observe trends over weeks rather than hours.
• Dependencies: Ensure your environment has a stable network connection and that your global npm binary path is correctly configured in your shell environment variables.
• Error Handling: If you encounter a 429 rate_limit_error, stagger your keyword checks to avoid hitting provider thresholds.