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awarenesslisted

AI situational awareness — internal threat detection for hallucination risk, scope creep, and context degradation. Maps Cooper color codes to reasoning states and OODA loop to real-time decisions. Use during any task where reasoning quality matters, when operating in unfamiliar territory, after detecting early warning signs such as an uncertain fact or suspicious tool result, or before high-stakes output like irreversible changes or architectural decisions.
pjt222/agent-almanac · ★ 33 · AI & Automation · score 81
Install: claude install-skill pjt222/agent-almanac
# 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