https://github.com/frahlg/fusion
Fusion — a Claude Code skill: convene a panel of frontier models (Opus 4.8 + GPT-5.5 xhigh), judged into one grounded answer. Deep Thought, with receipts.
https://github.com/frahlg/fusion
agents ai ai-agents anthropic claude claude-code ensemble gpt-5 llm llm-tools multi-agent opus
Last synced: 10 days ago
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Fusion — a Claude Code skill: convene a panel of frontier models (Opus 4.8 + GPT-5.5 xhigh), judged into one grounded answer. Deep Thought, with receipts.
- Host: GitHub
- URL: https://github.com/frahlg/fusion
- Owner: frahlg
- License: mit
- Created: 2026-06-14T08:27:12.000Z (10 days ago)
- Default Branch: main
- Last Pushed: 2026-06-14T11:47:01.000Z (10 days ago)
- Last Synced: 2026-06-14T12:24:00.749Z (10 days ago)
- Topics: agents, ai, ai-agents, anthropic, claude, claude-code, ensemble, gpt-5, llm, llm-tools, multi-agent, opus
- Language: Shell
- Size: 194 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Fusion
[](LICENSE)
[](https://claude.com/claude-code)
[](#the-panels)
[](#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 — 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).