SecondOpinion — AI Explanation Trust Layer

Problem: AI coding assistants explain code with total confidence — but those explanations can contradict themselves. One moment the AI says a function retries 3 times; the next, it says 5. A developer who trusts an inconsistent explanation ships bugs, security holes, and broken assumptions into production. Today there is no easy way to check whether an AI's explanation of code is stable and trustworthy. Solution: SecondOpinion is a trust layer for AI-assisted development. The user pastes any code snippet and selects the language; three specialist AI agents then explain the same code independently — one from a functionality perspective, one from a security perspective, and one in beginner-friendly terms. A fourth judge agent cross-checks the factual claims across all three explanations, flags contradictions in plain English ("Explanation A says X, but Explanation B says Y"), and computes a Stability Score from 0–100 (100 minus 25 per major contradiction, 10 per minor). The verdict is Trustworthy (80+), Use with Caution (50–79), or Unreliable (below 50). Clean code scores 100; confusing or subtly wrong code surfaces disagreements the developer would otherwise miss. Target users are developers, students, and teams who rely on AI coding assistants daily. They interact through a simple dark-themed web app: paste code, pick a language, click Check Stability, and read the score, verdict, contradictions, and all three explanations. What makes it creative and unique: instead of asking one AI for one answer, SecondOpinion applies explanation-stability and contradiction detection specifically to AI coding-assistant explanations — treating consistency itself as a measurable trust signal. The multi-agent cross-examination turns vague unease about AI reliability into a concrete, explainable score.