Task Completion Enforcer ProverをAIに接続

• 01 / 03How to audit refactoring
• 02 / 03ドキュメントの同期状態を検証する
• 03 / 03API実装の検証方法

最速日

770ms

最遅日

1026ms

14日間の傾向

安定+2%

Task Completion Enforcer Prover 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_TRZuombSa31k5jscX1KCJ089zhMtfMmLCTAbBgKK/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 — Task Completion Enforcer Prover capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "task-completion-enforcer-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_TRZuombSa31k5jscX1KCJ089zhMtfMmLCTAbBgKK/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？ Task Completion Enforcer Prover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

  ソフトウェアエンジニア

  LLMによるコード生成の正確性を担保し、TODOや未実装コードの混入を防ぎたい開発者。

• 02

  QAエンジニア

  AIが生成した成果物が、定義された要件をすべて満たしているかを自動的に検証したい担当者。

• 03

  プロジェクトマネージャー

  AIエージェントによるタスク実行が、指示通りに完遂されているかを厳格に管理したい管理者。

• 01

  What is Requirement Amnesia?

  It is when an AI forgets parts of your original request mid-task, delivering only a portion of what you asked for.

• 02

  How does this MCP stop placeholders?

  The capability identifies comments like TODO, FIXME, or TBD as failures, forcing the agent to replace them with real code before it can finish.

• 03

  Can I use this with Cursor or Windsurf?

  Yes, this MCP is compatible with any MCP-compatible client including Cursor, Windsurf, and VS Code.

• 04

  Does this capability do the work for the AI?

  No, it does not write code. It forces the agent to be honest about whether the code it wrote actually meets your requirements.

• 05

  What happens if the verification fails?

  If the capability detects a gap or a placeholder, it rejects the completion and instructs the agent to fix the specific issue and try again.

• 06

  Why do LLMs forget requirements?

  Autoregressive generation allocates decreasing attention to earlier tokens as output grows. A 10-step task at token 200 competes with 2,000 tokens of generated output for attention. The model literally loses track of requirement #7 while implementing requirement #3. The fix: force a re-read of ALL requirements before declaring completion.

• 07

  What counts as 'completion evidence'?

  Not 'I implemented the function.' Evidence means: 'Requirement 1: POST /users endpoint at src/routes/users.ts lines 15-42, validates email/name/role via Zod schema, returns 201 with user object.' File path, line number, specific behavior. If you cannot point to the exact artifact, it is not done.

• 08

  What happens when gaps are found?

  The LLM MUST close them immediately. not later, not in a follow-up. Do the remaining work NOW. Then call this capability AGAIN to verify the gaps are actually closed. The loop continues until EVERY requirement has concrete evidence. 'I will do it later' is rejected. 'I just did it, here is the evidence' is accepted.

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