Checking HIPAA Compliance
About
This skill automatically scans codebases, infrastructure, and documentation for potential HIPAA violations using the hipaa-compliance-checker plugin. It identifies issues related to data privacy, security controls, and PHI handling. Use it when you need to assess HIPAA readiness or check compliance for projects involving protected health information.
Quick Install
Claude Code
Recommended/plugin add https://github.com/jeremylongshore/claude-code-plugins-plusgit clone https://github.com/jeremylongshore/claude-code-plugins-plus.git ~/.claude/skills/Checking HIPAA ComplianceCopy and paste this command in Claude Code to install this skill
Documentation
Overview
This skill automates the process of identifying potential HIPAA compliance issues within a software project. By using the hipaa-compliance-checker plugin, it helps developers and security professionals proactively address vulnerabilities and ensure adherence to HIPAA guidelines.
How It Works
- Analyze Request: Claude identifies the user's intent to check for HIPAA compliance.
- Initiate Plugin: Claude activates the hipaa-compliance-checker plugin.
- Execute Checks: The plugin scans the specified codebase, configuration files, or documentation for potential HIPAA violations.
- Generate Report: The plugin generates a detailed report outlining identified issues and their potential impact on HIPAA compliance.
When to Use This Skill
This skill activates when you need to:
- Evaluate a codebase for HIPAA compliance before deployment.
- Identify potential HIPAA violations in existing systems.
- Assess the HIPAA readiness of infrastructure configurations.
- Verify that documentation adheres to HIPAA guidelines.
Examples
Example 1: Checking a codebase for HIPAA compliance
User request: "Check HIPAA compliance of the patient data API codebase."
The skill will:
- Activate the hipaa-compliance-checker plugin.
- Scan the specified API codebase for potential HIPAA violations.
- Generate a report listing any identified issues, such as insecure data storage or insufficient access controls.
Example 2: Assessing infrastructure configuration for HIPAA readiness
User request: "Assess the HIPAA readiness of our AWS infrastructure configuration."
The skill will:
- Activate the hipaa-compliance-checker plugin.
- Analyze the AWS infrastructure configuration files for potential HIPAA violations, such as misconfigured security groups or inadequate encryption.
- Generate a report outlining any identified issues and recommendations for remediation.
Best Practices
- Specify Target: Always clearly specify the target (e.g., codebase, configuration file, documentation) for the HIPAA compliance check.
- Review Reports: Carefully review the generated reports to understand the identified issues and their potential impact.
- Prioritize Remediation: Prioritize the remediation of identified issues based on their severity and potential impact on HIPAA compliance.
Integration
This skill can be integrated with other security and compliance tools to provide a comprehensive view of a system's security posture. The generated reports can be used as input for vulnerability management systems and security information and event management (SIEM) platforms.
GitHub Repository
Related Skills
sglang
MetaSGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.
evaluating-llms-harness
TestingThis Claude Skill runs the lm-evaluation-harness to benchmark LLMs across 60+ standardized academic tasks like MMLU and GSM8K. It's designed for developers to compare model quality, track training progress, or report academic results. The tool supports various backends including HuggingFace and vLLM models.
content-collections
MetaThis skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.
llamaguard
OtherLlamaGuard is Meta's 7-8B parameter model for moderating LLM inputs and outputs across six safety categories like violence and hate speech. It offers 94-95% accuracy and can be deployed using vLLM, Hugging Face, or Amazon SageMaker. Use this skill to easily integrate content filtering and safety guardrails into your AI applications.
