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ensemble-opinion
Get multi-model opinions on a problem (Codex + Gemini + Critic)
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
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Get multi-model opinions on a problem (Codex + Gemini + Critic)
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
Process autonomous task queue from do-work/ folder
Enter plan mode for complex tasks (pour energy into the plan for 1-shot implementation)
Initiate autonomous PR review process with Codex agent
Run comprehensive repo assessment with Codex (every 3 PRs)
Comprehensive security audit covering 10 threat categories
Install all automation for a new repo (git hooks + GitHub Actions)
| name | ensemble-opinion |
| description | Get multi-model opinions on a problem (Codex + Gemini + Critic) |
Created: 2026-02-09-00-00 Last Updated: 2026-02-09-00-00
You are orchestrating an ensemble of AI models to analyze a problem from multiple angles.
Review the conversation history and identify:
Restate the problem clearly and factually in 2-3 sentences. This exact problem statement will be sent to ALL models to ensure consistency.
If CODEX.md exists, read it and include relevant context in the problem statement.
Create ONE prompt that will be sent to all models. Structure:
Problem: [factual description - same for all models]
Context: [relevant codebase/project details from CODEX.md if exists]
Constraints: [any limitations]
Analyze this problem. Provide:
1. Your assessment of the situation
2. Risks and failure modes
3. Alternative approaches
4. Your recommendation
Be direct and critical. Identify blind spots.
Use the Task tool to spawn THREE agents simultaneously in a SINGLE message:
Codex Critic (subagent_type: codex_critic)
Gemini Agent (subagent_type: general-purpose)
echo '<UNBIASED_PROMPT>' | gemini 2>&1. If Gemini fails due to auth, return the error message."Codex Agent (subagent_type: general-purpose)
codex exec '<UNBIASED_PROMPT>' 2>&1 | tail -50. Return the model's response, stripping metadata headers."IMPORTANT: Launch all three Task tools in a SINGLE response so they run in parallel.
Once all three return, synthesize:
[The problem you identified]
What do multiple models agree on?
Where did they differ? Why?
What did none address?
Your integrated recommendation.