QA ArbiterをChatGPT、Claude、Geminiに接続

• 01 / 02テストエラーの判別方法
• 02 / 02トレースを検証する

最速日

627ms

最遅日

1142ms

14日間の傾向

安定-3%

QA Arbiter Connector

準備完了です。MCPクライアントを選択し、セットアップ手順に従ってください。

コネクタリンクhttps://edge.vinkius.com/vk_preview_X69TXPHsdjAfNffcyFTnx1dWNUhv3RVHL0mSZM7p/mcpコピー

Claude Desktop

以下の手順で数秒で接続できます。

1. 1In Claude Desktop, open Settings → Connectors.
2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3. 3Click Add and start a new chat — QA Arbiter capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "qa-arbiter-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_X69TXPHsdjAfNffcyFTnx1dWNUhv3RVHL0mSZM7p/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

各クライアントの手順ガイドはこちらです。 接続方法

Claude向けのガイド付きセットアップ？ QA ArbiterをClaudeや他のAIに設定する

このConnectorが対応するすべてのAIクライアントを見る ↑

• 01

  QAエンジニア

  テストの失敗がコードのバグによるものか、テスト定義のミスによるものかを迅速に判断したいプロフェッショナル。

• 02

  AIエージェント開発者

  自律型エージェントがテスト失敗時に迷走したり、無意味なリトライを繰り返したりするのを防ぎたいエンジニア。

• 03

  ソフトウェア開発者

  テストの誤りによる誤検知（偽陽性）を減らし、真のバグ修正に集中したい開発者。

• 01

  What is a Decision Pivot?

  It is a structured reasoning pattern where the agent must commit to two boolean values regarding whether the received and expected values match the execution trace.

• 02

  How does this prevent agents from guessing?

  The capability requires specific fields like the execution trace. If the agent's verdict contradicts its own trace, the capability rejects the answer, forcing the agent to re-analyze.

• 03

  Can I use this with Claude or Cursor?

  Yes, any MCP-compatible client like Claude, Cursor, or Windsurf can use this MCP once connected through Vinkius.

• 04

  Does the MCP actually run my code?

  No, the capability does not perform computations. It forces the agent to perform the computation and then validates that the agent's reasoning is internally consistent.

• 05

  What are the possible verdicts?

  The capability returns TEST_ERROR, ENGINE_DEFECT, BOTH_WRONG, or FALSE_ALARM.

• 06

  Does QA Arbiter run my tests or compute expected values?

  No. QA Arbiter performs zero computation and zero side effects. It forces the AI agent to structure its own reasoning into verifiable steps, then validates that the reasoning is logically consistent. Think of it as a reasoning enforcer. like Sequential Thinking, but specialized for test failure diagnosis.

• 07

  What are Decision Pivots?

  Decision Pivots are minimal, verifiable checkpoints that all correct reasoning paths must pass through. a concept from the ROMA research framework. In QA Arbiter, the two pivots are boolean fields: receivedMatchesTrace (does the engine's output match the hand-traced computation?) and expectedMatchesTrace (does the test's expected value match?). The verdict is derived deterministically from these two booleans, making it impossible to reach a wrong conclusion without contradicting yourself.

• 08

  How does it prevent pipeline deadlocks in multi-agent systems?

  In a typical QA→Developer pipeline, when tests fail, the system routes back to the developer. But if the tests themselves are wrong (QA's fault), the developer can't fix them. creating an infinite retry loop. QA Arbiter forces the QA agent to determine fault attribution BEFORE the pipeline routes: if it's TEST_ERROR, the QA agent fixes its own tests; if it's ENGINE_DEFECT, it routes to the developer with traced proof. The aggregate summary tells the orchestrator exactly what to do.

• 09

  What happens if the agent lies about the boolean pivots?

  The consistency validation catches direct contradictions. e.g., if the agent says both values match the trace but chose TEST_ERROR instead of FALSE_ALARM, the capability rejects it. For subtler misrepresentations, the engineTrace field creates an auditable trail: post-hoc analysis can cross-reference the trace against the actual engine source code. The structured format makes deception mechanically harder than with free-form text.

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