Magi test

Skill weiting-tw/MAGI-System/skills/magi-test

MAGI System — Inspired by Evangelion's MAGI supercomputer. Three AI engines (Claude, Gemini, Codex) analyze tasks in parallel, then reach consensus through voting. A Claude Code skills plugin.

Install

npx -y skills add weiting-tw/MAGI-System --skill magi-test

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What its author says it does

Copied from the file, not written here

三機(Claude/Gemini/Codex)平行審查測試，評估覆蓋率、邊界條件、異常處理後投票共識

SKILL.md

1.7 KB, 686 tokens by cl100k_base, as published. Nobody here has run it

MAGI Test 快捷指令

/magi-test [feature] - 測試覆蓋評估

此指令為 /magi test [feature] 的快捷方式。

使用方式

/magi-test 用戶登入功能
/magi-test src/services/payment.ts

執行內容

自動啟動 MAGI 三機平行分析：

機體	引擎	分析重點
MELCHIOR-1	Claude Sonnet	測試策略、覆蓋完整性
BALTHASAR-2	Gemini Flash	測試品質、Mock 使用合理性、測試隔離性
CASPER-3	Codex/GPT	安全測試覆蓋、負面測試、邊界條件

🚨 強制執行規則

<MANDATORY> 執行此指令時，必須嚴格遵守以下規則：

禁止事項：

❌ 禁止委派給其他 agent 處理
❌ 禁止使用非指定的工具

必須使用：

✅ MELCHIOR-1: Task tool with subagent_type="general-purpose", model="sonnet"
✅ BALTHASAR-2: mcp__gemini__ask-gemini (先用 ToolSearch 載入)
✅ CASPER-3: mcp__codex-cli__ask-codex (先用 ToolSearch 載入)

執行步驟：

先以單一 ToolSearch 載入 MCP 工具：ToolSearch(query="select:mcp__gemini__ask-gemini,mcp__codex-cli__ask-codex")
在單一訊息中同時發出三個 tool calls（Task + Gemini + Codex）
等待三機回應後彙整共識報告 </MANDATORY>

模型設定（test 任務）

機體	模型	參數
MELCHIOR-1	`sonnet`	-
BALTHASAR-2	`gemini-3-flash-preview`	-
CASPER-3	`gpt-5.2-codex`	`reasoningEffort: "medium"`

完整的投票機制與共識報告格式，見主 skill magi（skills/SKILL.md）。

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.