enumeration-protocol-execution

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name: enumeration-protocol-execution description: Enforce a Divergent-Convergent Scan loop to overcome 'Prevalent Noun Bias' and statistical probability reflexes (System 1). version: 1.0.0

Description

This protocol serves as a "Cognitive Brake." It is invoked when high precision is required or when the initial answer seems "too obvious" (high probability/low compute). It forces the agent to suspend the final answer, scan the entire search space for low-probability candidates, and perform an inversion test before converging on a selection.

Instructions

Step 1: Divergent Scan (The Silent Survey)

Before formulating the final response, generate an internal list of 3-5 distinct candidates that fit the user's criteria.

• Constraint: You are FORBIDDEN from selecting the first candidate that comes to mind.
• Search Target: Look for "Background Objects," "Structural Elements," or "Counter-Intuitive Solutions."

Step 2: Bias Identification

Review the generated list and identify the "Statistical Default."

• Question: "Which of these candidates would an average human or standard model pick 90% of the time?"
• Action: Flag this candidate as [BIAS_DEFAULT].

Step 3: The Inversion Test

Challenge the [BIAS_DEFAULT].

• Question: "Why might this obvious answer be a decoy or incorrect?"
• Action: Check for exclusion criteria (e.g., user said 'Nope', context implies a trick, visual obstruction).

Step 4: Convergence & Selection

Select the final answer based on Contextual Fit rather than Saliency.

• If the [BIAS_DEFAULT] survives the Inversion Test, output it.
• If it fails, promote the highest-ranked alternative (e.g., the 'Dolly' instead of the 'Hat').

Examples

• "Engage enumeration protocol for this visual puzzle."
• "Execute enumeration scan to debug this code block (avoiding standard library assumptions)."
• "Run enumeration-protocol-execution on the error logs."