Multi-Brain Score Protocol

Add quantified confidence scoring to any multi-brain decision. Each perspective rates its own confidence, and the consensus uses scores as decision weights. Uncertainty becomes visible instead of hidden.

Workflow

1. Run base multi-brain (3 perspectives)
2. Each instance scores its confidence (1-10)
3. Weighted consensus based on scores
4. Flag uncertainty zones
5. Produce full output with scores visible

Step 1: Perspectives with Scores

Each instance provides their perspective plus a confidence score:

## 🧠 Brainstorm (Scored)

**Instance A — Creative:** (Confidence: 6/10)
[2-3 sentences]
_Confidence rationale: Novel approach but limited precedent in production._

**Instance B — Pragmatic:** (Confidence: 9/10)
[2-3 sentences]
_Confidence rationale: Well-established pattern, used this successfully before._

**Instance C — Comprehensive:** (Confidence: 7/10)
[2-3 sentences]
_Confidence rationale: Good coverage of risks but missing data on edge case X._

Step 2: Score Analysis

Before consensus, analyze the confidence landscape:

## 📊 Confidence Analysis

| Instance | Score | Strength | Weakness |
|----------|-------|----------|----------|
| A — Creative | 6/10 | High potential impact | Unproven approach |
| B — Pragmatic | 9/10 | Battle-tested | May miss innovation |
| C — Comprehensive | 7/10 | Risk-aware | Incomplete data |

**Average Confidence:** 7.3/10
**Spread:** 3 points (moderate disagreement)
**Highest Confidence:** Instance B

Step 3: Weighted Consensus

Use confidence scores to weight the consensus:

• High confidence (8-10): This perspective's core recommendation carries heavy weight.
• Medium confidence (5-7): Consider as a modifier or secondary input.
• Low confidence (1-4): Flag as an area needing more research before deciding. Do not ignore — surface it as a risk.

## ⚖️ Weighted Consensus

**Primary direction:** [Based on highest-confidence perspective]
**Modified by:** [Elements from medium-confidence perspectives]
**Flagged for research:** [Low-confidence areas that need validation]

**Overall Decision Confidence:** [Weighted average]/10

Step 4: Uncertainty Flags

If any perspective scores below 5, or if the spread between scores is > 4:

> ⚠️ **Uncertainty Alert:** [Description of what is uncertain and what would resolve it]

Step 5: Full Output

Mandatory: The final response must include all scored perspectives, the confidence analysis table, the weighted consensus, any uncertainty flags, and the complete deliverable.

Scoring Rubric

Guardrails

• Always show scores inline with perspectives — they are part of the deliverable.
• Confidence rationale is mandatory — a bare number without explanation is useless.
• Never inflate scores — honest uncertainty is more valuable than false confidence.
• If all scores are below 5, recommend more research before deciding instead of forcing a weak consensus.
• Scores should create action items — low scores become "things to validate."
• This protocol can be combined with base multi-brain or multi-brain-experts.

References

• See references/EXAMPLES.md for scored decision examples.

🔗 Next Steps & Handoffs

Ecosystem: @ecosystem-reasoning — Reasoning, Planning Gates & Prompting.

Workflows:

• Decision Quality Flow (reason-decision, step 4 of 5): next → @output-critic (optional).

Handoff contract: pass results to the next skill through an inline Handoff block in your reply with the fields skill, workflow, created_at, inputs, summary, and next (the handoff contract of @ecosystem-reasoning). If a next skill is not installed, continue with its step from the ecosystem map, or install it with npx skills add fatih-developer/fth-skills --skill <name> after the user agrees.