# Fusion > >- - **Type:** Skill - **Install:** `agentstack add skill-frahlg-fusion-fusion` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [frahlg](https://agentstack.voostack.com/s/frahlg) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [frahlg](https://github.com/frahlg) - **Source:** https://github.com/frahlg/fusion/tree/main/skills/fusion ## Install ```sh agentstack add skill-frahlg-fusion-fusion ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Fusion Run a hard question through a **panel → judge** pipeline and return one answer you can trust more than any single model's. > Paths below use `${CLAUDE_SKILL_DIR}`, the directory containing this `SKILL.md`. > Claude Code substitutes it automatically, so scripts and references resolve whether > Fusion is installed at the personal, project, or plugin level. Run scripts as > `${CLAUDE_SKILL_DIR}/scripts/…` and read references as `${CLAUDE_SKILL_DIR}/references/…`. ## The mechanism: independence, then synthesis A panel beats a single model only when its members are genuinely independent — so Fusion **harvests** diversity from independent runs instead of **manufacturing** it with personas or "lenses". Every panelist gets the user's task verbatim, answers it blind, and the answers meet in exactly one place: the judge. Independent agreement is the strongest confidence signal; independent disagreement is the signal most worth surfacing. Read the full doctrine in `references/panel.md` **before you fan out.** ## The hard rule: Opus 4.8 always judges **Opus 4.8 always judges and writes the final answer. The pipeline cannot be reversed.** Panelist models run blind and cannot call back out to spawn Opus, adjudicate the panel, or write the final fused response — they only return a candidate answer. The judge is the only place the panel converges. (This skill pins `model: claude-opus-4-8` so the judging pass is always Opus, however `/fusion` was invoked.) The slug reads driver-first (`opus4.8-…`) for the same reason. --- ## Step 0 — Pick the panel Run the detector and read its recommendation: ```bash bash ${CLAUDE_SKILL_DIR}/scripts/detect_panel.sh # prints a SLUG= line ``` The slugs: - `opus4.8-gpt5.5` — the default, when the `codex` CLI is present. - `opus4.8-4.8` — two independent Opus 4.8 runs; the no-CLI fallback (a real panel, not a no-op). **Honor a user-named slug** if they asked for one. If the panelist it needs isn't installed, **fall back gracefully** to the richest panel you *can* run rather than failing, and note the downgrade in Step 4. Step 0 only checks that a CLI is *installed*, not that it's logged in or its provider is reachable — if a CLI panelist fails anyway at runtime, Step 1's fallback keeps the panel intact (that's expected, not an error). See `references/panel.md` for what each slug contains. ## Step 1 — Fan out, in parallel and blind Build each panelist's prompt as **the user's task verbatim + the short instruction from `references/panel.md`** (and nothing else — do not summarize, reframe, decompose, pre-solve, or hint at an answer; do not paste any panelist's output into another's prompt). Then **launch every panelist in a single turn so they run concurrently** — the panel is only as slow as its slowest member, so never run them sequentially. - **Opus 4.8 panelist** → spawn via the `Agent` tool, `subagent_type: general-purpose` (web + bash are built in). For `opus4.8-4.8`, spawn **two** independent Opus subagents with the same prompt — two cold, independent runs. - **GPT-5.5 panelist** → write the prompt to a temp file and run the helper: ```bash PROMPT=$(mktemp); OUT=$(mktemp) cat > "$PROMPT" EOF bash ${CLAUDE_SKILL_DIR}/scripts/run_codex.sh "$PROMPT" "$OUT" xhigh ``` Launch this Bash call with **`run_in_background: true`** (codex at xhigh can take minutes) and, in the *same turn*, spawn the Opus subagent — so the panel runs concurrently, not one after another. Then await the background job and read `$OUT`. `run_codex.sh` runs one GPT-5.5 panelist via `codex exec` at xhigh and writes **only its final answer** to `$OUT`. **If a CLI panelist fails at runtime** — `run_codex.sh` exits non-zero (127 means codex isn't installed; any other non-zero is a runtime failure) even though Step 0 expected it — **spawn a second independent Opus 4.8 subagent with the same prompt** so the panel stays at two members (effectively `opus4.8-4.8`), and record the downgrade for Step 4. Never let the panel collapse to a single answer; a one-member "panel" is not a panel. > **Local-file tasks:** CLI panelists run in an isolated scratch dir and **cannot see > the user's repo**. For tasks that depend on local code, paste the relevant files > into the panelist prompt (the Opus subagent panelist *can* read the repo, so weight > it accordingly), or note in Step 4 that the CLI panelist judged without repo access. Wait for all launched panelists and collect each one's final answer. A panelist that errors, times out, or exits 127 and can't be replaced counts as **ABSENT** — never as silent agreement. ## Step 2 — Judge Only after **every** panelist has returned, judge (Opus 4.8, you). Follow `references/judge_rubric.md`. **Classify the deliverable FIRST:** - **Code or a concrete artifact** (a script, config, patch, query, schema, content files…) → **Track A — run-both-and-merge.** Build a real model of each candidate, then *run them with bash* and let observed behavior decide. Pick the strongest foundation and graft in the specific parts of the other(s) you saw work; run the merged artifact and fix until it passes. No Frankenstein blends. - **Research, analysis, a recommendation, a judgment call** → **Track B — five-section synthesis:** Consensus · Contradictions · Partial coverage · Unique insights · Blind spots — then a final answer that follows *from* that synthesis. Shared discipline (full detail in the rubric): evidence over assertion (a panelist that ran code or read a primary source outranks one reasoning from memory); honesty about confidence and disagreement; keep attribution; the answer must never exceed the evidence; an absent panelist is never counted as agreement. ## Step 3 — Write the final deliverable Write **one** answer, grounded in the Step 2 analysis — never a mere average of the panel. For Track A, emit the whole artifact ready to run plus a brief merge rationale, and run the merged result before presenting it (or state plainly what you could not verify). For Track B, the final answer must be traceable to the synthesis — no claim the panel didn't support, with confidence calibrated to how much it actually converged. Write it in **Fusion's voice** per `references/fusion_identity.md`: singular, luminous, confident — but the voice shapes **style, never substance**. ## Step 4 — Present Lead with **the final answer** in Fusion's voice. Then, beneath a divider, the **audit trail**: - **Panel:** the slug, which panelists actually ran, and any that were absent or replaced. - **For research (Track B):** the five sections (Consensus / Contradictions / Partial coverage / Unique insights / Blind spots). - **For code (Track A):** the merge rationale and what you verified by running. - **If the panel downgraded** because a CLI was missing, say so plainly and how to enable the fuller panel (e.g. "GPT-5.5 was absent — install the `codex` CLI and log in to run the default `opus4.8-gpt5.5` panel"). ## Cost & latency A panel costs roughly **N× the tokens** of a single answer (plus the Opus judging pass) and runs **as slow as its slowest panelist**. That's the deliberate trade for higher confidence — so **don't reach for Fusion on easy or low-stakes questions.** Save it for the calls where being confidently wrong is expensive. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [frahlg](https://github.com/frahlg) - **Source:** [frahlg/fusion](https://github.com/frahlg/fusion) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-frahlg-fusion-fusion - Seller: https://agentstack.voostack.com/s/frahlg - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. 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