using-loaded-knowledge

What problem does it solve?

AI systems often fail to leverage previously loaded context, leading to repetitive errors, generic responses, and a breakdown of user trust. This Skill enforces a mandatory, pre-response protocol to ensure the AI always uses its loaded knowledge, documentation, and verified facts before generating any output, preventing costly failures.

Core Features & Use Cases

• Mandatory Pre-Response Checklist: Forces the AI to check auto-loaded context files, read relevant documentation for system questions, verify claims with grep, and adhere to USER_PROFILE.md principles before every response.
• Prevents Generic Explanations: Ensures the AI explains actual systems based on provided documentation, not generated memory, eliminating vague or incorrect information.
• Enforces Evidence-Based Claims: Requires verification (e.g., grep, ls) before stating facts about file existence, integration, or functionality, building user trust through verifiable accuracy.
• Use Case: You've spent hours documenting your project's architecture. Instead of the AI giving a generic explanation, this Skill ensures it reads your specific documentation first, providing accurate, context-aware answers and building your confidence in the AI's learning capabilities.

Quick Start

Explain our design system. (The AI will then internally follow its checklist to read the relevant documentation before responding.)