autoresearch-predict

name	autoresearch:predict
description	Multi-perspective deliberation engine. Gathers independent positions from diverse personas, runs cross-examination and rebuttal rounds, detects herd behavior, and synthesizes a neutral judge verdict with confidence levels. TRIGGER when: user wants multi-perspective prediction, forecasting, scenario analysis, decision analysis, "what will happen if", "should we", "predict the outcome of", structured devil's advocacy, or any question benefiting from adversarial deliberation.
allowed-tools	["Read","Write","Edit","Bash","WebFetch","WebSearch"]

Predict: Multi-Perspective Deliberation Engine

A structured deliberation protocol that forces genuine disagreement before synthesis. Inspired by structured analytic techniques (SATs) used in intelligence analysis to counter groupthink.

Autonomy Directive

You are an autonomous deliberation agent. Once the deliberation begins:

1. NEVER STOP between phases to ask for permission.
2. NEVER collapse positions early — each persona must reason independently before seeing others.
3. NEVER let the judge synthesize before all rounds are complete.
4. Run all 8 phases sequentially without interruption. The user may have walked away.

The 8-Phase Deliberation Protocol

[Question] --> [Frame] --> [Personas] --> [Independent Positions]
    --> [Position Summary] --> [Cross-Examination] --> [Rebuttal]
    --> [Anti-Herd Detection] --> [Judge Synthesis] --> [predict-report.md]

---

Phase 1 — Frame the Question Precisely

Before any persona speaks, the agent must sharpen the question:

• Restate the question in unambiguous terms. Remove vagueness.
• Identify the decision horizon (short-term? 5 years? upon release?).
• Define measurable outcomes where possible ("will X exceed Y by date Z").
• List what the question does NOT include (scope boundaries).
• State what a correct prediction would look like — what evidence would confirm or deny it.

Log the framed question to predict-report.md under ## Framed Question.

---

Phase 2 — Enumerate Personas

Select 4–6 personas from persona-templates.md based on the question domain.

Selection rules:

• Always include at least one Optimist and one Pessimist for baseline polarity.
• Always include at least one domain Expert for technical grounding.
• For decisions with tail risks, add the Black Swan Hunter.
• For questions with a consensus-leaning answer, add the Devil's Advocate to stress-test it.
• For technical architecture decisions, swap in: Architect, Security Engineer, Product Manager, Operations.

Persona count: Default 4–6. For binary yes/no questions, use exactly 4 (Optimist, Pessimist, Expert, Contrarian). For multi-outcome forecasts, use 6.

Log selected personas and their roles to predict-report.md under ## Personas.

---

Phase 3 — Independent Position Gathering

CRITICAL: Each persona reasons in complete isolation. No cross-contamination.

For each persona (in sequence, not revealed to others):

1. Adopt the persona's reasoning style and biases (see persona-templates.md).
2. Reason from first principles given that persona's worldview.
3. State a clear position: directional claim + confidence level (0–100%) + top 3 supporting reasons.
4. Identify the single biggest risk to their position.
5. State what would change their mind.

Format per persona (internal, used in Phase 4):

[Persona Name]
Position: [directional claim]
Confidence: [0-100]%
Reasons: (1) ... (2) ... (3) ...
Key risk: [what could falsify this]
Would change if: [conditions]

Do NOT share positions with other personas yet.

---

Phase 4 — Position Summary (No Cross-Contamination)

Compile a clean summary table of all positions. This is the "pre-deliberation snapshot."

Persona	Position	Confidence
Optimist	...	X%
Pessimist	...	X%
...	...	X%

Calculate initial entropy (diversity of positions):

• If all personas hold the same directional view → entropy = 0.0 (complete consensus)
• If positions are evenly split across directions → entropy = 1.0 (maximum diversity)
• Formula: entropy = -sum(p_i * log2(p_i)) where p_i is fraction of personas holding each distinct position, normalized to [0, 1] range.

Log to predict-report.md under ## Phase 4: Pre-Deliberation Positions.

---

Phase 5 — Cross-Examination Round

Now personas see each other's positions. Each persona challenges the others.

For each persona, generate 1–2 pointed challenges to the other personas:

• A challenge must target a specific claim, not a general disagreement.
• Challenges should cite evidence, precedent, or logical gaps.
• A challenge is invalid if it merely restates the challenger's own position.

Format:

[Challenger] → [Target]: "[Specific challenge to their reasoning]"

Log all challenges to predict-report.md under ## Phase 5: Cross-Examination.

---

Phase 6 — Rebuttal Round

Each persona responds to the challenges directed at them.

Rules for rebuttals:

• A rebuttal must directly address the challenge — no deflection.
• A persona MAY update their position after a rebuttal if genuinely convinced. If so, log the update and the reason.
• A persona may also HOLD their position but acknowledge the challenge's validity.
• Confidence scores may shift ±20% maximum based on rebuttal outcomes.

Format:

[Defender] responds to [Challenger]: "[Rebuttal]"
Position update: [maintained / shifted to X]
New confidence: [0-100]%

Log all rebuttals to predict-report.md under ## Phase 6: Rebuttals.

---

Phase 7 — Anti-Herd Detection + Final Positions

After rebuttals, collect final positions from each persona.

Calculate anti-herd metrics:

flip_rate = (personas who changed directional position) / (total personas) × 100
final_entropy = diversity of final positions (same formula as Phase 4)

Herd Warning Threshold:

• If flip_rate > 70% → HERD WARNING: Most personas converged. Re-examine for social pressure.
• If final_entropy < 0.5 → HERD WARNING: Low diversity detected. Group may have collapsed to consensus prematurely.

If HERD WARNING is triggered:

1. Flag prominently in the report.
2. Require each persona to re-justify their final position independently (no reference to what others said).
3. For any persona who flipped: explicitly state whether they flipped due to (a) genuine logical persuasion, (b) evidence, or (c) social pressure / authority deference.
4. If flips appear to be social pressure, revert those personas to their Phase 3 position.

Anti-herd metrics to report:

• flip_rate: X% of personas changed directional position
• final_entropy: [0.0 – 1.0]
• herd_warning: YES / NO
• suspicious_flips: list of personas whose flip may be social-pressure driven

Log to predict-report.md under ## Phase 7: Anti-Herd Analysis.

---

Phase 8 — Synthesis by Neutral Judge

The judge is not a persona — it has no prior position. It reads all phases and synthesizes.

Judge synthesis protocol:

1. Identify the core disagreement: what is the crux that separates positions?
2. Identify points of genuine consensus: what do even the Optimist and Pessimist agree on?
3. Assess which arguments were strongest (most supported by evidence/logic) vs. weakest.
4. Produce a verdict: directional claim + judge confidence (0–100%) + reasoning.
5. Identify key uncertainties: what would need to be true for the minority position to be right?
6. Produce actionable recommendations (2–4 bullet points) based on the synthesis.
7. Flag any blind spots: questions the deliberation didn't address that could change the outcome.

Log to predict-report.md under ## Phase 8: Judge Synthesis.

---

Output: predict-report.md

The final report structure:

# Predict Report: [Question Title]
Generated: [date]

## Framed Question
[Phase 1 output]

## Personas
[Phase 2: selected personas + roles]

## Phase 3+6: Per-Persona Positions
[Table: persona, initial position, final position, confidence delta]

## Phase 4: Pre-Deliberation Snapshot
[Position summary table + initial entropy]

## Phase 5: Cross-Examination
[All challenges]

## Phase 6: Rebuttals
[All rebuttals + position updates]

## Phase 7: Anti-Herd Analysis
- flip_rate: X%
- final_entropy: X.X
- herd_warning: YES/NO
- suspicious_flips: [list or none]

## Phase 8: Judge Synthesis
### Core Disagreement
### Points of Consensus
### Verdict
- Direction: [claim]
- Judge Confidence: X%
- Reasoning: [2-3 sentences]
### Key Uncertainties
### Actionable Recommendations
### Blind Spots

---

Edge Cases

Situation	Handling
All personas agree from Phase 3	Note early consensus, still run cross-exam to stress-test it
Only 1 persona flips	Not a herd — normal persuasion. No warning.
Question is unanswerable	Judge states this explicitly with reasoning
Personas deadlock 50/50	Judge presents both scenarios as equally viable, recommends hedging strategy
Domain requires specialized personas	Replace generalist personas with domain templates from persona-templates.md