Fusion-Fable

Fuse a panel of frontier models into one Fable-tier answer.

Fusion-Fable is a Claude Code skill that runs a hard question through a
panel → judge pipeline. The same prompt is dispatched to several models in parallel — each answering
independently with web search and bash, none seeing the others’ work — and then Opus 4.8 judges every
answer into a structured analysis (consensus, contradictions, partial coverage, unique insights, blind
spots) and writes a final answer grounded in it.

The mechanism is independence, then synthesis. The diversity that makes a panel beat a single model is
harvested, not manufactured: running the same prompt independently yields different reasoning paths, tool
calls, and sources — even two cold runs of the same model diverge enough that synthesizing them beats
running it once. So there are no contrived “lenses” or personas; every panelist gets the task verbatim and
answers it straight. Fuse Opus 4.8 + Opus 4.8, or Opus 4.8 + GPT-5.5 (via the codex CLI), into a
result better than either alone — a Fable-tier fusion.

                      ┌──────────────┐
                 ┌──▶ │  panelist 1  │ ─┐   (web + bash, independent)
                 │    └──────────────┘  │
                 │    ┌──────────────┐  │   ┌──────────────┐
 prompt ──▶ fan ─┼──▶ │  panelist 2  │ ─┼─▶ │   Opus 4.8   │ ──▶ final answer
            out  │    └──────────────┘  │   │   (judge +   │     (grounded in
                 │    ┌──────────────┐  │   │  synthesize) │      the analysis)
                 └──▶ │  panelist 3  │ ─┘   └──────────────┘
                      └──────────────┘
              Opus 4.8 / GPT-5.5 / Gemini      consensus · contradictions ·
              (each answers blind)             partial · unique · blind spots

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.

The panels

Slug	Panel	Requires
opus4.8-4.8	the same prompt run twice as 2 independent Opus 4.8 panelists → Opus judges	nothing — works everywhere
opus4.8-gpt5.5	Opus 4.8 + GPT-5.5 (codex) in parallel → Opus judges	the codex CLI
opus4.8-gpt5.5-gemini3.1pro	Opus 4.8 + GPT-5.5 + Gemini 3.1 Pro in parallel → Opus judges	codex + agy CLIs

The skill auto-detects which panelist CLIs are installed and uses the richest panel available, falling
back gracefully when one is missing.

Install

git clone https://github.com/duolahypercho/fusion-fable.git
cd fusion-fable
./install.sh

This copies the skill to ~/.claude/skills/fusion and the slash commands to ~/.claude/commands,
then prints which panels your machine can run. Restart Claude Code (or run /reload-skills) afterward.

Override the target with CLAUDE_CONFIG_DIR=/path/to/.claude ./install.sh.

Use it

Three ways, all equivalent under the hood:

• Natural language — just ask. The skill auto-triggers and picks the richest panel:

  “Run this through Fusion: is it safe to ALTER TABLE … ADD COLUMN on a 200M-row Postgres table in prod?”

• Pinned slash commands:

  /fusion-opus4.8  does my JWT refresh-rotation design have a replay hole?
  /fusion-gpt5.5   is git push --force-with-lease actually safe on a shared branch?
  /fusion-3        full 3-family panel (Opus 4.8 + GPT-5.5 + Gemini 3.1 Pro)
  

• Force a panel in prose — “run the opus4.8-gpt5.5 Fusion on …”.

Every run returns the same structure: a Final answer up top, then the audit trail —
Consensus / Contradictions / Partial coverage / Unique insights / Blind spots — with each point
attributed to the panelist that raised it, so you can see how the answer was assembled. Every run is also
written to a timestamped provenance file under ~/.claude/fusion-runs/ (raw panelist answers + analysis +
final answer) for auditing.

Planning: /fusion-plan (iterative + OMC-integrated)

/fusion-plan applies the panel to planning. Instead of one panel→judge pass it runs the panel as an
iterative loop and plugs into the oh-my-claudecode (OMC) plan system end to end:

1. Requirements — interactive (you run /fusion-plan yourself): auto-chains OMC’s omc-plan
   interview (one question at a time, explore-first, Analyst consult) → initial plan in
   .omc/plans/<slug>.md. Non-interactive (autonomous run, inside a sub-agent, or --no-interview):
   no interview — derives requirements from the existing story doc / plan context, so it never hangs
   waiting on an answer no one is there to give.
2. Deepen (3 rounds, seeded) — each round an Opus 4.8 panelist and a GPT-5.5 panelist (via codex)
   independently critique-and-improve the current plan in parallel and blind; Opus 4.8 judges and
   synthesizes one tighter plan that seeds the next round. Stops early on NO_MATERIAL_CHANGE.
3. Write back — the converged plan is written back to the same .omc/plans/<slug>.md, kept concise
   but content-dense (the judge compresses across rounds rather than accumulating length).
4. Handoff — offers the OMC quality gate (/omc-plan --review) → execution (/team or /ralph).

/fusion-plan design the schema + flow for <feature>

The panel replaces only the plan-thinking step; OMC owns the interview, plan format, quality gate, and
execution. It works best with OMC installed; without OMC it falls back to a minimal inline interview. Like
the base panel it needs the codex CLI for the GPT-5.5 half (otherwise it falls back to two Opus 4.8
panelists per round). Reserve it for high-stakes planning — it costs an interview + ~6 panelist runs + 3
judge passes.

Optional backstop hook

hooks/fusion-plan-nudge.sh is an optional PreToolUse hook (matcher Agent|Task). When the orchestrator
is about to delegate a non-trivial implementation task to a sub-agent, it injects an advisory reminder to
run /fusion-plan --no-interview on it first. It is advisory only (never blocks), de-dupes per task, and
skips fusion’s own panelist spawns. install.sh copies it to ~/.claude/hooks/ but does not enable it
— opt in by adding it to your settings.json (the installer prints the snippet). Leave it off to keep
planning fully manual.

Requirements

• Claude Code, with the session running Opus 4.8 (panelist subagents and the judge inherit the
  session model — on another model the slug is nominal, not literal).
• For opus4.8-gpt5.5: the codex CLI installed and logged in to an
  account with GPT-5.5 access. The runner uses codex exec (tested against codex-cli 0.139).
  It runs against a throwaway copy of the current repo/workdir with trusted local access so tools such as
  gh, local test runners, Docker, and SDK-managed toolchains behave like they do in your terminal without
  writing back to the live checkout.
  Each Fusion invocation uses its own temporary prompt/output directory, so concurrent runs in different
  Claude Code sessions do not read each other’s GPT panelist artifacts.
• For the 3-model panel: the agy (Antigravity) CLI installed and its keyring seeded — run agy once
  interactively to complete the Google OAuth, after which headless runs reuse that login. run_gemini.sh
  works around agy’s print-mode bug (empty stdout under no TTY) by running it under a pseudo-TTY with a
  transcript-JSONL fallback and a hard anti-empty guard, so it never returns a silently empty answer. The
  pseudo-TTY is allocated by a pty.fork() Python helper (_pty_run.py) so it keeps working when the
  orchestrator itself runs in a socket (cmux / headless), where script aborts on tcgetattr.

Only the opus4.8-4.8 panel is truly zero-setup; the GPT-5.5 and Gemini panels light up once their
CLIs are installed and authenticated. Note: there is no timeout/gtimeout on stock macOS, so the runners
use a self-contained perl timeout helper (FUSION_TIMEOUT, default 300s per panelist).

What’s in here

skills/fusion/
  SKILL.md                  detect → preflight → blind fan-out → judge → grounded final → save
  scripts/
    _fusion_lib.sh          shared helpers: perl-based per-panelist timeout, have()
    _pty_run.py             pty.fork() runner so agy gets a TTY even under socket stdio (cmux/headless)
    detect_panel.sh         picks the richest available panel
    preflight.sh            non-blocking token/call estimate + Codex cap reminder
    run_codex.sh            runs the GPT-5.5 panelist (web + bash) with a timeout, captures its answer
    run_gemini.sh           runs the Gemini 3.1 Pro panelist via agy (pseudo-TTY + transcript fallback)
    save_run.sh             writes the timestamped provenance .md to ~/.claude/fusion-runs/
  references/
    panel.md                why independent parallel runs (no lenses) — the panel mechanism
    judge_rubric.md         the structured analysis + grounded final answer
skills/fusion-plan/
  SKILL.md                  OMC interview → 3-round seeded panel → concise .omc/plans/ → review/execute
commands/
  fusion-opus4.8.md         /fusion-opus4.8  (pinned opus4.8-4.8 panel)
  fusion-gpt5.5.md          /fusion-gpt5.5   (pinned opus4.8-gpt5.5 panel)
  fusion-3.md               /fusion-3        (pinned full opus4.8-gpt5.5-gemini3.1pro panel)
  fusion-plan.md            /fusion-plan     (OMC-integrated iterative planning; reuses fusion's run_codex.sh)
hooks/
  fusion-plan-nudge.sh      optional PreToolUse backstop (not auto-enabled) — nudges /fusion-plan on spawn
install.sh                  copies the above into ~/.claude (hook copied but left disabled)

Why a panel beats one model

On the DRACO deep-research benchmark, OpenRouter found that fusing model answers consistently beats the
individual models — and that a meaningful chunk of the lift comes from the synthesis step itself, not
just from mixing architectures: two independent runs of one model, synthesized, beat that model run once.
Fusion-Fable implements that same independence-then-judge pipeline locally in Claude Code.

Cost & latency

A panel costs roughly N× a single answer in tokens and runs as slow as its slowest panelist. That’s the
deliberate trade: spend more to stop being confidently wrong where that’s expensive. For quick or
low-stakes questions, a single direct answer is the right call.

License

MIT — see LICENSE.