# Fusion [![License: MIT](https://img.shields.io/badge/License-MIT-black.svg)](LICENSE) [![Claude Code skill](https://img.shields.io/badge/Claude%20Code-skill-d97757)](https://claude.com/claude-code) [![Panel](https://img.shields.io/badge/panel-Opus%204.8%20%2B%20GPT--5.5-blue)](#the-panels) [![Answer](https://img.shields.io/badge/answer-42-9cf)](#the-panels) **Stop trusting one model. Convene a panel.** Fusion is a [Claude Code](https://claude.com/claude-code) skill for questions where a single model answer is too cheap to trust. It runs your hardest prompt through a **panel → judge** pipeline: several frontier models answer *in parallel and blind*, then Opus 4.8 judges every answer and forges one you can actually trust — with the full audit trail underneath. > *Deep Thought ran for 7½ million years and returned a single number. Fusion runs a panel of frontier models > and returns one grounded answer — plus the receipts.*

An illustrative /fusion run: an Opus 4.8 + GPT-5.5 (xhigh) panel answers blind, then Opus judges into one verdict with a consensus / contradictions / blind-spots audit trail

An illustrative /fusion run — verdict first, audit trail underneath.

**The counterintuitive part:** you don't need *different* models to beat one model. Even two cold runs of the *same* model diverge — different reasoning paths, different searches, different mistakes — and synthesizing that divergence beats running it once. Fusion harvests that diversity instead of faking it with personas or "lenses". ``` ┌──────────────┐ ┌──▶ │ panelist 1 │ ─┐ (web + bash, independent) │ │ Opus 4.8 │ │ prompt ──▶ fan ─┤ └──────────────┘ ├─▶ ┌──────────────┐ out │ ┌──────────────┐ │ │ Opus 4.8 │ ──▶ Fusion's └──▶ │ panelist 2 │ ─┘ │ (judge + │ final answer │ GPT-5.5 │ │ synthesize) │ (grounded in │ (xhigh) │ └──────────────┘ the analysis) └──────────────┘ each answers blind consensus · contradictions · partial · unique · blind spots ``` Many great minds computing toward one answer — except this answer ships with receipts, disagreement, and its own confidence boundaries. Opus 4.8 **always** judges and writes the final answer; the pipeline can't be reversed, because the panelist models can't call back out to spawn Opus. ## What an answer looks like Fusion always leads with the verdict, then shows its work (illustrative): ```text > /fusion Single MQTT broker or a quorum for our edge control loop? Run the quorum. Every independent line of reasoning converged here: a single broker is a single point of failure your control loop can't survive, and the latency cost of consensus stays inside your 200 ms budget. One real caveat — no panelist could verify failover time under network partition, so prove that on your hardware before you trust it in production. ────────────────────────────────────────────────────────────── Panel: opus4.8-gpt5.5 — Opus 4.8 ✓ · GPT-5.5 (xhigh) ✓ Consensus · quorum for availability; latency fits the 200 ms budget Contradictions · broker count (3 vs 5) — adjudicated to 3 on the cited benchmark Unique insight · GPT-5.5 flagged split-brain on even-sized clusters Blind spots · failover-under-partition timing unverified by either panelist ``` The verdict you can read in ten seconds. The audit trail is there for when being wrong is expensive. ## The panels | Slug | Panel | Requires | | --- | --- | --- | | `opus4.8-gpt5.5` | Opus 4.8 + **GPT-5.5 (xhigh)** in parallel → Opus judges | the `codex` CLI | | `opus4.8-4.8` | the **same prompt run twice** as 2 independent Opus 4.8 panelists → Opus judges | nothing — works everywhere (fallback) | The skill auto-detects whether the `codex` CLI is installed and usable, and falls back gracefully to the pure-Opus panel when it isn't. The default is **Opus 4.8 + GPT-5.5 (xhigh)**. *Two independent minds in; one answer out. Deep Thought only had the one.* ## When to use it Reach for Fusion when one model being **confidently wrong** would cost you more than an extra model pass: - architecture and design calls - high-stakes research - gnarly / incident debugging - vendor or framework decisions - claims that need sources, commands, or cross-checking Skip it for the easy stuff — Fusion is deliberately slower and more expensive than one model. ## Install ```bash git clone https://github.com/frahlg/fusion.git cd fusion ./install.sh ``` This copies the skill to `~/.claude/skills/fusion` and prints which panels your machine can run. The skill is itself invocable as `/fusion`, so no separate command file is needed. Restart Claude Code (or run `/reload-skills`) afterward. > Override the target with `CLAUDE_CONFIG_DIR=/path/to/.claude ./install.sh`. ## Use Run one hard prompt: ``` /fusion Should we run our edge control loop on a single MQTT broker or a quorum? ``` …or just ask in prose to "run it through Fusion" / "ask the panel". Fusion returns the final answer first, then the audit trail (Consensus / Contradictions / Partial coverage / Unique insights / Blind spots) so you can trace every claim back to a panelist. Don't panic about the cost: a panel runs roughly N× the tokens of a single answer and is as slow as its slowest panelist. That's the deliberate trade for an answer worth trusting — not a default. ## Requirements - Claude Code with Opus 4.8 (judge + an always-available panelist via subagents). - Optional: the [`codex`](https://github.com/openai/codex) CLI for the GPT-5.5 (xhigh) panelist. Without it, Fusion runs the pure-Opus `opus4.8-4.8` panel. ## License MIT — see [LICENSE](LICENSE).