Compliance Checker logo

Compliance Checker

Organization
OneWave-AI
compliance-checker

Audits a codebase or business process for regulatory compliance across GDPR, HIPAA, SOC2, CCPA, and PCI-DSS. Scans for PII handling, data retention, encryption, access controls, audit logging, consent management, and data transfer issues. Generates a structured compliance report with findings, gap analysis, remediation steps, and evidence requirements.

Overview

PublisherOneWave-AI
Repositoryclaude-skills
Skill namecompliance-checker
Stars
293
Forks
49
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by OneWave-AI on GitHub. Read the source before you install it.

Installation

Install the Compliance Checker AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/OneWave-AI/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/compliance-checker .claude/skills/compliance-checker
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Compliance Checker in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Compliance Checker on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Compliance Checker is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Compliance Checker

Perform thorough regulatory compliance audits against one or more frameworks, identify gaps, and produce actionable remediation guidance with evidence requirements suitable for certification preparation.

Contents

  • references/frameworks.md — the five supported frameworks (GDPR, HIPAA, SOC 2, CCPA, PCI-DSS): scope, key articles/requirements, penalties, and reference links.
  • references/scan-patterns.md — the seven scan categories, their search patterns, scan execution rules, and common pitfalls to always check.
  • references/classification.md — compliance status values, risk severity rubric, and the remediation detail fields.
  • references/cross-framework-mapping.md — control-area-to-framework mapping and the glossary.
  • references/output-template.md — the full compliance-report.md structure, including per-framework gap-analysis tables and evidence packs.

Workflow

Run the full methodology for every audit. Do not skip steps.

Phase 1: Discovery and Scoping

  1. Identify the target: codebase, infrastructure configuration, business process documentation, or a combination.
  2. Determine applicable frameworks from the data types processed, geographic scope, industry, and business model. See references/frameworks.md. When none are specified, assess all five and note applicability.
  3. Map the data flow: where regulated data enters, how it is processed, where it is stored, and how it exits.
  4. Inventory data categories present (PII, PHI, CHD, sensitive PI, special category data).

Phase 2: Scanning and Evidence Collection

  1. Scan each of the seven categories — PII/sensitive data, data retention, encryption, access controls, audit logging, consent management, and data transfer. Apply the search patterns and execution rules in references/scan-patterns.md. Record exact file paths, line numbers, and snippets for both positive findings and gaps.

Phase 3: Gap Analysis

  1. Map each finding to specific framework requirements, assign a compliance status, and assign a risk severity to every non-compliant or partial finding. Use the rubric in references/classification.md.

Phase 4: Remediation Planning

  1. For each non-compliant or partial finding, produce the remediation detail (description, regulatory reference, current state, required state, steps, evidence, effort, dependencies) per references/classification.md. Cross-reference references/cross-framework-mapping.md to flag when one action closes gaps across multiple frameworks.

Phase 5: Report Generation

  1. Generate compliance-report.md in the project root (or a user-specified location), following the mandatory structure in references/output-template.md. Every section is required; if a section has no findings, state that explicitly.

Behavioral Rules

  1. Never fabricate findings. Back every finding with scan evidence. When evidence is absent, mark UNABLE TO ASSESS rather than guess.
  2. Be specific. Reference exact file paths, line numbers, function names, and configuration keys.
  3. Distinguish technical from organizational controls. Note when a finding requires verifying organizational controls (training, policies, physical security) that code review alone cannot confirm.
  4. Consider the full stack: application code, database schemas, infrastructure configuration, CI/CD pipelines, dependency manifests, documentation, and environment configuration.
  5. Prioritize actionable findings. Specify exact changes; avoid vague recommendations like "improve security".
  6. Respect the scope. Audit only what is provided. Do not assume broader infrastructure without evidence.
  7. Account for frameworks and libraries that handle compliance concerns (ORM parameterized queries, framework CSRF protection); credit them as positive findings but verify configuration.
  8. Avoid false positives. Missing a marginal finding is better than reporting a non-gap. Err toward accuracy.
  9. Cross-reference across frameworks. Note when a single remediation addresses multiple regulations.
  10. Date and version everything so the report can be compared against future audits.

Responding to Requests

  • "Audit this codebase" / "check compliance": Confirm which frameworks to focus on (or assess all five), run Phases 1-5, generate compliance-report.md, and summarize the most critical findings.
  • "Check for [framework]": Focus on that framework, still scan all seven categories, and map findings only to it.
  • "Check [category]" (e.g., "check encryption"): Focus the scan on that category and map findings to all applicable frameworks.
  • "Are we [requirement] compliant?" (e.g., GDPR Art. 17): Focus on the relevant controls, give a direct assessment with evidence, and offer remediation if gaps exist.
  • Business process documentation instead of code: Adapt the methodology to document analysis, focus on policy and procedure requirements, and note that technical controls cannot be verified without codebase access.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Compliance Checker AI skill do?

Audits a codebase or business process for regulatory compliance across GDPR, HIPAA, SOC2, CCPA, and PCI-DSS. Scans for PII handling, data retention, encryption, access controls, audit logging, consent management, and data transfer issues. Generates a structured compliance report with findings, gap analysis, remediation steps, and evidence requirements.

Why use Compliance Checker on TypingMind?

Because you install it once and use it with any model. Compliance Checker is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Compliance Checker in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OneWave-AI/claude-skills/tree/main/compliance-checker. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Compliance Checker?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Compliance Checker?

As many as you like. As long as a model supports skills, you can use Compliance Checker with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Compliance Checker AI skill free?

Yes. It is published on GitHub by OneWave-AI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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