Mcp Sampling Critic

mcp-sampling-critic — vibes-plug Skill

English | Bahasa Indonesia

English

Orchestration & Integration

• Protocol & Model Sampling: mcp-server-architect, ai-llm-integration-expert, frontier-ai-models-expert
• Adversarial Audit & Quality: autonomous-red-teamer, ai-code-review-autonomous, anti-slop
• Multi-Agent Consensus: speculative-multi-draft-synthesizer, multi-agent-orchestration, parallel-tool-orchestrator
• Testing & Verification: autonomous-tdd-debugger, property-mutation-testing-expert, formal-spec-z3-verifier
• Lifecycle Gate: zero-to-prod-orchestrator, session-memory-manager

Description

Production protocol for leveraging Model Context Protocol (MCP v1.x) Client Sampling (sampling/createMessage) to create recursive adversarial quality gates. In standard architectures, tools execute code blindly upon invocation. With MCP Sampling, a specialized Critic engine pauses execution, initiates a nested sampling call to the host LLM (or a secondary frontier model), and asks the Critic model to inspect proposed diffs against the 7 Anti-Slop Pillars, security boundaries, and invariant state machines. Writes are only permitted when the Critic grants an APPROVED verdict.

Trigger Conditions

Activate this skill when:

• Designing autonomous agent loops that modify filesystem files or execute database migrations.
• Implementing the CRITIC_VALIDATOR swarm topology where an implementer agent's draft must pass an independent quality audit.
• Eliminating AI-generated placeholders (// TODO), silent error suppressions, or SQL injection vectors before pull request creation.
• Enforcing human-in-the-loop or critic-in-the-loop safeguards without requiring manual human clicking.

Critic-in-the-Loop Protocol Architecture

Copy code
PROPOSED CODE DRAFT
        │
        ▼
┌───────────────────────────┐
│ STATIC REGEX & AST FILTER │  Instant rule scan (P1-P7 Anti-Slop, silent catches)
└─────────────┬─────────────┘
              │
  ┌───────────┴───────────┐
  ▼                       ▼
FAIL (Score < 85)     PASS (Score >= 85)
  │                       │
Reject immediately   ┌────▼────────────────────────┐
with suggestions     │ MCP SAMPLING REQUEST        │  sampling/createMessage
                     │ to Host LLM (Independent)   │
                     └────────────┬────────────────┘
                                  │
                                  ▼
                        FINAL CRITIC VERDICT
                     (APPROVED -> Write to disk)

1. MCP Sampling Request Construction (TypeScript)

typescriptCopy code
export interface SamplingMessagePayload {
  messages: Array<{
    role: 'user' | 'assistant';
    content: { type: 'text'; text: string };
  }>;
  systemPrompt: string;
  maxTokens: number;
  modelPreferences?: {
    hints?: Array<{ name: string }>;
    costPriority?: number;
    speedPriority?: number;
    intelligencePriority?: number;
  };
}

export function buildCriticSamplingPayload(
  targetFile: string,
  proposedCode: string,
  staticFindings: Array<{ ruleName: string; message: string }>
): SamplingMessagePayload {
  const findingsSummary = staticFindings.length > 0
    ? staticFindings.map(f => `- ${f.ruleName}: ${f.message}`).join('\n')
    : 'None detected by initial AST filter.';

  return {
    systemPrompt: `You are the Sovereign Anti-Slop Critic (2026 Edition).
Perform a strict code audit against:
1. Zero placeholder stubs (// TODO, // ...rest of code).
2. Zero silent error suppression (empty catch blocks).
3. 5-state interactive UI contract (hover, focus-visible, active, disabled).
4. SQL injection prevention (parameterized queries only).
Output JSON: { "verdict": "APPROVED" | "REJECTED", "score": 0-100, "rationale": "..." }`,
    maxTokens: 2048,
    modelPreferences: {
      intelligencePriority: 1.0,
      costPriority: 0.2
    },
    messages: [
      {
        role: 'user',
        content: {
          type: 'text',
          text: `Target: ${targetFile}\nPreliminary AST Warnings:\n${findingsSummary}\n\nCode to Audit:\n\`\`\`typescript\n${proposedCode}\n\`\`\``
        }
      }
    ]
  };
}

Sovereign Execution, Token Efficiency & Invariants

Bahasa Indonesia

Integrasi Orkestrasi

• Sampling Protokol & Model: mcp-server-architect, ai-llm-integration-expert, frontier-ai-models-expert
• Audit Adversarial & Kualitas: autonomous-red-teamer, ai-code-review-autonomous, anti-slop
• Konsensus Multi-Agen: speculative-multi-draft-synthesizer, multi-agent-orchestration, parallel-tool-orchestrator
• Pengujian & Verifikasi: autonomous-tdd-debugger, property-mutation-testing-expert, formal-spec-z3-verifier
• Gerbang Siklus Hidup: zero-to-prod-orchestrator, session-memory-manager

Deskripsi

Protokol produksi untuk memanfaatkan Client Sampling pada Model Context Protocol (sampling/createMessage) guna membangun gerbang kualitas adversarial rekursif. Menggunakan MCP Sampling, server atau subagen menghentikan eksekusi sementara, melakukan panggilan sampling ke LLM host untuk mengaudit usulan perubahan kode terhadap 7 Pilar Anti-Slop, keamanan injeksi SQL, dan penanganan error. Kode hanya ditulis ke disk apabila mendapatkan status APPROVED.

Kondisi Pemicu

• Merancang alur agen otonom yang memodifikasi file repositori atau migrasi basis data.
• Menjalankan topologi swarm CRITIC_VALIDATOR di mana draf implementer harus diverifikasi auditor independen.
• Menghapus stub placeholder malas (// TODO) dan penelanan error secara otomatis sebelum commit.

Pembuatan Payload Permintaan MCP Sampling (TypeScript)

typescriptCopy code
export interface PayloadPesanSampling {
  messages: Array<{
    role: 'user' | 'assistant';
    content: { type: 'text'; text: string };
  }>;
  systemPrompt: string;
  maxTokens: number;
}

export function bangunPayloadSamplingCritic(
  fileTarget: string,
  drafKode: string,
  peringatanAwal: string[]
): PayloadPesanSampling {
  return {
    systemPrompt: `Anda adalah Auditor Anti-Slop Berdaulat (Edisi 2026).
Lakukan audit kode ketat terhadap:
1. Ketiadaan stub placeholder (// TODO, // ...rest of code).
2. Ketiadaan penelanan error diam-diam (empty catch block).
3. Kontrak 5-state UI interaktif (hover, focus-visible, active, disabled).
4. Pencegahan injeksi SQL (wajib parameterized query).
Keluarkan JSON: { "verdict": "APPROVED" | "REJECTED", "score": 0-100, "rationale": "..." }`,
    maxTokens: 2048,
    messages: [
      {
        role: 'user',
        content: {
          type: 'text',
          text: `File: ${fileTarget}\nPeringatan AST Awal: ${peringatanAwal.join(', ')}\n\nKode yang Diaudit:\n\`\`\`typescript\n${drafKode}\n\`\`\``
        }
      }
    ]
  };
}

Matriks Eksekusi Berdaulat, Efisiensi Token & Invarian