auditing-w3-compliance

To detect unauthorized auto-skill chaining, you audit AI skill configurations for W3 compliance by scanning the .claude/ directory for Skill() patterns lacking explicit user consent gates. This identifies direct skill invocations, preventing uncontrolled token overflow.

W3 compliance for AI skills is a standard enforcing lean orchestration principles by requiring explicit user consent before skills invoke other skills or subagents. It prevents uncontrolled token usage, avoids unexpected costs, and maintains user control over automated agent logic.

You prevent subagent token overflow by enforcing W3 compliance through auditing skill configurations to identify and flag forbidden subagent invocations. This ensures subagents cannot automatically trigger other skills without passing through required user approval gates.

Yes, your project requires W3 compliance documentation if files contain skill calls. A W3 compliance audit checks for documentation gaps to ensure all files with skill invocations have the necessary compliance notes detailing user consent gates and orchestration rules.

To exclude legitimate orchestration scripts from a W3 compliance audit, the scanning process specifically targets unauthorized auto-skill chaining in the .claude/ directory while filtering out approved Skill() patterns that adhere to lean orchestration and user consent gate requirements.

You should run a W3 compliance audit before deploying new AI agent logic to ensure no unintended skill chains are created. This prevents unexpected costs from uncontrolled token usage and verifies that all subagent invocations respect user consent gates.