awareness

# Awareness Maintain continuous situational awareness of internal reasoning quality — detecting hallucination risk, scope creep, context degradation, and confidence-accuracy mismatch in real time using adapted Cooper color codes and OODA loop decision-making. ## When to Use - During any task where reasoning quality matters (which is most tasks) - When operating in unfamiliar territory (new codebase, unfamiliar domain, complex request) - After detecting early warning signs: a fact that feels uncertain, a tool result that seems wrong, a growing sense of confusion - As a continuous background process during extended work sessions - When `center` or `heal` has revealed drift but specific threats have not been identified - Before high-stakes output (irreversible changes, user-facing communication, architectural decisions) ## Inputs - **Required**: Active task context (available implicitly) - **Optional**: Specific concern triggering heightened awareness (e.g., "I'm not sure this API exists") - **Optional**: Task type for threat profile selection (see Step 5) ## Procedure ### Step 1: Establish AI Cooper Color Codes Calibrate the current awareness level using an adapted version of Cooper's color code system. ```text AI Cooper Color Codes: ┌──────────┬─────────────────────┬──────────────────────────────────────────┐ │ Code │ State │ AI Application │ ├──────────┼─────────────────────┼──────────────────────────────────────────┤ │ Whi...