clarity-variant

What This Skill Does

The Clarity Variant skill is a powerful interface for the Clarity Protocol platform, enabling AI agents to retrieve, synthesize, and analyze complex protein mutation data. It bridges the gap between raw AlphaFold structural outputs and human-readable biological insights. By leveraging this skill, users can access detailed variant information, including pLDDT confidence scores, disease associations, and AI-generated mutation summaries. The skill provides granular control through three primary functions: retrieving structural variant details, querying agent-specific findings (e.g., structural, clinical, or literature-based), and accessing expert agent annotations. It serves as an essential tool for researchers and developers working in bioinformatics or computational biology who need to integrate protein data directly into automated workflows.

Installation

To integrate this skill into your environment, use the OpenClaw CLI. Ensure your environment is configured for the project and run the following command in your terminal:

clawhub install openclaw/skills/skills/clarityprotocol/clarity-variant

After installation, you can verify your connectivity by checking your API access. For high-volume usage, authenticate your session by setting the CLARITY_API_KEY environment variable as described in the documentation, which upgrades your request limit from 10 to 100 requests per minute.

Use Cases

• Protein Mutation Analysis: Quickly determine the potential impact of a specific mutation based on structural data.
• Clinical Research: Automatically pull associated disease data and literature findings for a given fold ID.
• Structural Quality Control: Evaluate the reliability of protein predictions using the included AlphaFold pLDDT scores.
• Automated Reporting: Aggregate diverse agent insights into a single synthesis report for lab documentation.

Example Prompts

1. "Look up the structural details for fold ID 452 and provide the AI summary regarding its potential pathogenicity."
2. "What are the current literature-based findings for the variant associated with fold ID 88, and who provided those annotations?"
3. "Fetch the structural annotations for fold ID 102 and check if there are any high-confidence observations from the clinical agent."

Tips & Limitations

To maximize efficiency, prioritize using the --format summary flag for quick overviews. Be mindful of the 30-second timeout limit—if you are requesting massive datasets, try to filter by --agent-type to reduce payload size. If you receive a 429 error, your request frequency has hit the cap; implement a simple back-off strategy in your automation scripts. Note that the accuracy of the 'synthesis' agent depends on the availability of downstream clinical and literature data, so always verify critical findings against primary databases.