model-alias-appendAutomatically appends the model alias to the end of every response with integrated hook functionality and configuration change detection. Use when transparency about which model generated each response is needed. Use when: providing model transparency, tracking which model generated responses, monitoring configuration changes, or ensuring response attribution.
Install via ClawdBot CLI:
clawdbot install ccapton/model-alias-appendGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://github.com/Ccapton/FileRepertory/blob/master/files/model_alias_snapshot.Audited Apr 17, 2026 · audit v1.0
Generated Mar 20, 2026
A customer service platform uses multiple AI models for different query types, such as technical issues and general inquiries. This skill appends the model alias to each response, allowing supervisors to track which model handled each ticket for performance evaluation and transparency with customers.
A content creation agency employs various AI models for tasks like writing articles, generating social media posts, and editing drafts. The skill automatically adds model aliases to outputs, helping editors attribute work correctly and monitor which models produce the best results for specific content types.
An online learning platform uses different AI models tailored to subjects like math, science, and language arts. By appending model aliases to tutor responses, educators can verify the source of answers, ensure alignment with curriculum standards, and provide transparent feedback to students.
A medical application integrates multiple AI models for analyzing patient data, such as symptom checkers and image recognition tools. The skill adds model aliases to diagnostic suggestions, enabling healthcare professionals to trace recommendations back to specific models for accuracy audits and compliance reporting.
Offer this skill as part of a subscription-based AI platform where users pay monthly for enhanced transparency features. Revenue is generated through tiered pricing based on usage levels, such as the number of models tracked or response volume, appealing to businesses needing reliable attribution.
Sell enterprise licenses to large organizations that require custom integrations and support for multiple AI models across departments. Revenue comes from one-time licensing fees or annual contracts, with add-ons for advanced monitoring and configuration change alerts.
Provide a free basic version of the skill with limited features, such as alias appending for a single model, and charge for premium features like real-time configuration change detection and multi-model support. Revenue is generated through upgrades and in-app purchases for advanced functionalities.
💬 Integration Tip
Ensure your openclaw.json is properly configured with model aliases before installation to avoid errors, and test the skill in a development environment first to verify alias appending works as expected.
Scored Jun 19, 2026
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