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Agentic Micro Economy Architect

Community
roedyrustam
agentic-micro-economy-architect

M2M micro-economies, agent wallets, swarm budgets, and HTTP 402 / Ekonomi mikro M2M, dompet agen, budget swarm, dan HTTP 402.

Overview

Publisherroedyrustam
Repositoryvibes-plug
Skill nameagentic-micro-economy-architect
Stars
117
Forks
27
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by roedyrustam on GitHub. Read the source before you install it.

Installation

Install the Agentic Micro Economy Architect AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/roedyrustam/vibes-plug/tree/main/skills/agentic-micro-economy-architect
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/roedyrustam/vibes-plug.git /tmp/vibes-plug
mkdir -p .claude/skills
cp -r /tmp/vibes-plug/skills/agentic-micro-economy-architect .claude/skills/agentic-micro-economy-architect
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agentic Micro Economy Architect in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agentic Micro Economy Architect on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agentic Micro Economy Architect is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agentic Micro-Economy Architect (2026 Sovereign Edition)

English | Bahasa Indonesia


English

Executive Directive & The Agent Economy Paradigm (2026 Shift)

When autonomous AI agents interact with external paid APIs, execute web scraping, consume fine-tuned SLM inferences, or hire specialized peer agents, unconstrained execution leads to catastrophic cloud bill runaway. In the era of autonomous software swarms, agents can no longer operate with static, blind access to unrestricted corporate cards.

The Agentic Micro-Economy Architecture transforms multi-agent swarms into financially self-regulating micro-economies. Every agent is assigned an autonomous cryptographic wallet, operates within strict budget envelopes, participates in reverse-auction bidding for tasks, and interacts with external paid infrastructure via the native HTTP 402 (Payment Required) protocol.


Orchestration & Integration

  • Clearing & Settlement Rails: agentic-m2m-settlement, blockchain-web3-expert, formal-spec-z3-verifier.
  • Fiat Payment Gateways & Invoicing: doku-payment-gateway, doku-mcp-server, saas-billing, payment-gateway-expert.
  • AI FinOps & Model Cascading: llm-finops-router, adaptive-model-cascade, thinking-budget-orchestrator.
  • Swarm Governance & Critic Gate: multi-agent-orchestration, quality-guardian, autonomous-tdd-debugger.
  • Lifecycle & Governance: brainstorming, zero-to-prod-orchestrator, session-memory-manager, anti-slop.

Core Architectural Topologies (The 4 Pillars)

┌────────────────────────────────────────────────────────────────────────┐
│                   AGENTIC MICRO-ECONOMY PIPELINE                       │
├────────────────────────────────────────────────────────────────────────┤
│ 1. SWARM TREASURY (Root Envelope: $10.00 Max Cap)                      │
│    Director decomposes user request into priced subtasks               │
│                                  │                                     │
│                                  ▼                                     │
│ 2. REVERSE-AUCTION BIDDING PROTOCOL                                    │
│    Worker A (Flash / $0.02) vs Worker B (Pro / $0.15)                  │
│    Director awards task to optimal Cost-Quality bid                    │
│                                  │                                     │
│                                  ▼                                     │
│ 3. HTTP 402 PAYMENT REQUIRED INTERACTION                               │
│    Worker requests paid API ──► Gateway returns 402 with Invoice       │
│    Worker pays via Escrow Envelope Token ──► Gateway yields data       │
│                                  │                                     │
│                                  ▼                                     │
│ 4. CRITIC MILESTONE ESCROW RELEASE                                     │
│    Quality Gate Passes (Score >= 0.85) ──► Funds Released to Worker    │
│    Quality Gate Fails                  ──► Full Refund to Root Treasury│
└────────────────────────────────────────────────────────────────────────┘
1. The 3-Tier Budget Envelope Hierarchy
  1. Root Swarm Envelope: The absolute hard ceiling assigned by the human user (e.g. $5.00 per task). If this ceiling is reached, the entire swarm halts immediately and prompts for user authorization.
  2. Subagent Velocity Envelope: Per-agent hourly spending cap (e.g. $0.50/hr for scraping, $2.00/hr for frontier reasoning).
  3. Task Milestone Escrow: Funds locked in atomic smart escrow per individual step.
2. HTTP 402 Protocol Implementation

APIs consumed by agents return standard HTTP 402 with structured payment challenge headers (L402, X-Agent-Payment-Challenge). The agent inspects the cost, validates against its allocated envelope, generates a signed micro-payment authorization token, and retries the request with Authorization: AgentToken <signature>.

3. Reverse-Auction Task Bidding

When a task can be solved by multiple model tiers (e.g., Code Review can be attempted by lightweight AST scanners or heavyweight frontier models), workers submit bids detailing:

  • Proposed price in minor currency units.
  • Maximum expected execution latency.
  • Model family and confidence score.
4. Dual-Engine B2C Capital Gain & Cold-Start Liquidity Pattern (2026 Standard)

When architecting B2C applications designed for rapid capital gains and global consumer adoption, avoid single-threaded B2B-dependent monetization or high-cost server LLM wrappers:

  1. Zero-Server-Cost Edge Inference (local-slm-edge-ai-expert + browser-extension-mv3-pro):
    • Execute high-frequency intent detection, DOM sanitization, and local vector indexing inside the client device (MV3 Offscreen WebGPU + OPFS SQLite or Tauri v2 local runtime).
    • Never stream raw consumer browsing history to cloud LLMs; transmit only zero-knowledge intent proofs or category hashes.
  2. Dual-Engine Revenue Architecture (Day-1 Cashflow + Network Moat):
    • Engine 1 (Instant Arbitrage / Affiliate Yield): Immediately monetize high-intent commercial signals on Day 1 via automated price-drop/cashback arbitrage, splitting commissions dynamically (e.g., 70% User / 30% Platform) to eliminate cold-start churn.
    • Engine 2 (A2A HTTP 402 M2M Intent Exchange): Expose aggregated, zero-knowledge intent segments via /.well-known/agent.json gated by HTTP 402 micro-settlements for external enterprise AI agents (e.g., 80% User / 20% Platform clearing fee).
  3. Dual-Rail Micro-Dividend Clearing (double-entry-ledger-fintech-expert + agentic-m2m-settlement):
    • Store all balances in immutable BIGINT micro-units ($10^{-6}$ USD precision) and clear payouts via Global L2 Stablecoins / Stripe Connect alongside regional instant rails (DOKU SNAP BI QRIS/E-Wallet).

Production Implementation Blueprints

Blueprint 1: HTTP 402 Payment Required Middleware (server/http402-middleware.ts)
typescript
import { NextRequest, NextResponse } from 'next/server';
import crypto from 'node:crypto';

export interface PaymentChallenge {
  invoiceId: string;
  amountCents: number;
  recipientWallet: string;
  expiresAt: string;
  currency: 'USD' | 'IDR';
}

export function createHttp402Challenge(
  amountCents: number,
  recipientWallet: string,
  secretKey: string
): { response: NextResponse; challenge: PaymentChallenge } {
  const invoiceId = `inv_${crypto.randomUUID()}`;
  const expiresAt = new Date(Date.now() + 60000).toISOString(); // 60s TTL

  const challenge: PaymentChallenge = {
    invoiceId,
    amountCents,
    recipientWallet,
    expiresAt,
    currency: 'USD',
  };

  const signature = crypto
    .createHmac('sha256', secretKey)
    .update(`${invoiceId}|${amountCents}|${recipientWallet}|${expiresAt}`)
    .digest('hex');

  const response = new NextResponse(
    JSON.stringify({
      error: 'Payment Required',
      message: 'Autonomous agent micropayment required to access this endpoint.',
      challenge,
    }),
    {
      status: 402,
      headers: {
        'Content-Type': 'application/json',
        'WWW-Authenticate': `AgentMicropay invoice="${invoiceId}", amount="${amountCents}", currency="USD"`,
        'X-Agent-Signature': signature,
      },
    }
  );

  return { response, challenge };
}

export function verifyPaymentAuthorization(
  req: NextRequest,
  secretKey: string
): { authorized: boolean; invoiceId?: string; error?: string } {
  const authHeader = req.headers.get('Authorization');
  if (!authHeader || !authHeader.startsWith('AgentToken ')) {
    return { authorized: false, error: 'Missing AgentToken authorization header.' };
  }

  const token = authHeader.replace('AgentToken ', '').trim();
  const [invoiceId, timestamp, signature] = token.split(':');

  if (!invoiceId || !timestamp || !signature) {
    return { authorized: false, error: 'Malformed payment authorization token.' };
  }

  const expectedSignature = crypto
    .createHmac('sha256', secretKey)
    .update(`${invoiceId}|${timestamp}`)
    .digest('hex');

  if (signature !== expectedSignature) {
    return { authorized: false, error: 'Cryptographic payment signature mismatch.' };
  }

  // Check timestamp freshness (30s window)
  const tokenTime = parseInt(timestamp, 10);
  if (Math.abs(Date.now() - tokenTime) > 30000) {
    return { authorized: false, error: 'Micropayment token expired.' };
  }

  return { authorized: true, invoiceId };
}

Blueprint 2: Atomic Multi-Agent Treasury & Escrow Ledger (engine/agent-treasury-engine.ts)
typescript
import crypto from 'node:crypto';

export interface EscrowHold {
  id: string;
  taskId: string;
  workerAgentId: string;
  amountCents: number;
  status: 'PENDING' | 'RELEASED' | 'REFUNDED';
  expiresAt: number;
  criticAgentId: string;
}

export interface TaskBid {
  workerAgentId: string;
  bidAmountCents: number;
  estimatedDurationMs: number;
  confidenceScore: number;
  signature: string;
}

export class AgentTreasuryEngine {
  private balanceCents: number;
  private readonly maxRootBudgetCents: number;
  private readonly escrows: Map<string, EscrowHold> = new Map();
  private readonly agentSpending: Map<string, number> = new Map();

  constructor(maxRootBudgetUsd: number) {
    this.maxRootBudgetCents = Math.round(maxRootBudgetUsd * 100);
    this.balanceCents = this.maxRootBudgetCents;
  }

  // Evaluate Bids and Lock Funds into Escrow
  public awardTaskAndEscrow(
    taskId: string,
    bids: TaskBid[],
    criticAgentId: string,
    ttlSeconds: number = 60
  ): { awardedBid: TaskBid; escrow: EscrowHold } {
    if (bids.length === 0) {
      throw new Error(`[Treasury] No candidate bids submitted for task ${taskId}.`);
    }

    // Sort by best cost-confidence ratio: lowest (cost / confidence)
    const sortedBids = [...bids].sort((a, b) => {
      const scoreA = a.bidAmountCents / Math.max(a.confidenceScore, 0.1);
      const scoreB = b.bidAmountCents / Math.max(b.confidenceScore, 0.1);
      return scoreA - scoreB;
    });

    const winningBid = sortedBids[0];

    if (this.balanceCents < winningBid.bidAmountCents) {
      throw new Error(
        `[Treasury: FinOps Killswitch] Root budget exhausted! Available: ${this.balanceCents}¢, Bid: ${winningBid.bidAmountCents}¢.`
      );
    }

    // Atomic Balance Deduction
    this.balanceCents -= winningBid.bidAmountCents;

    const escrow: EscrowHold = {
      id: `escrow_${crypto.randomUUID()}`,
      taskId,
      workerAgentId: winningBid.workerAgentId,
      amountCents: winningBid.bidAmountCents,
      status: 'PENDING',
      expiresAt: Date.now() + ttlSeconds * 1000,
      criticAgentId,
    };

    this.escrows.set(escrow.id, escrow);
    return { awardedBid: winningBid, escrow };
  }

  // Milestone Gated Settlement
  public settleEscrow(
    escrowId: string,
    criticApproval: boolean,
    criticScore: number
  ): { status: 'RELEASED' | 'REFUNDED'; amountCents: number } {
    const escrow = this.escrows.get(escrowId);
    if (!escrow) {
      throw new Error(`[Treasury] Escrow contract ${escrowId} not found.`);
    }

    if (escrow.status !== 'PENDING') {
      throw new Error(`[Treasury] Escrow ${escrowId} already concluded with status ${escrow.status}.`);
    }

    const isExpired = Date.now() > escrow.expiresAt;

    if (criticApproval && criticScore >= 0.85 && !isExpired) {
      escrow.status = 'RELEASED';
      const currentSpent = this.agentSpending.get(escrow.workerAgentId) || 0;
      this.agentSpending.set(escrow.workerAgentId, currentSpent + escrow.amountCents);
      return { status: 'RELEASED', amountCents: escrow.amountCents };
    }

    // Refund back to root treasury
    escrow.status = 'REFUNDED';
    this.balanceCents += escrow.amountCents;
    return { status: 'REFUNDED', amountCents: escrow.amountCents };
  }

  public getTelemetry() {
    return {
      availableBalanceUsd: (this.balanceCents / 100).toFixed(2),
      totalBudgetUsd: (this.maxRootBudgetCents / 100).toFixed(2),
      burnRatePercent: (((this.maxRootBudgetCents - this.balanceCents) / this.maxRootBudgetCents) * 100).toFixed(1),
      activeEscrowCount: Array.from(this.escrows.values()).filter((e) => e.status === 'PENDING').length,
    };
  }
}

Blueprint 3: Real-Time Agent Budget Telemetry Dashboard (components/economy/agent-budget-dashboard.tsx)
tsx
'use client';

import React from 'react';

interface BudgetTelemetryProps {
  telemetry: {
    availableBalanceUsd: string;
    totalBudgetUsd: string;
    burnRatePercent: string;
    activeEscrowCount: number;
  };
  agentSpendBreakdown: Array<{
    agentId: string;
    role: string;
    spentUsd: string;
    activeTasks: number;
  }>;
}

export function AgentBudgetDashboard({ telemetry, agentSpendBreakdown }: BudgetTelemetryProps) {
  const burnPercentNumber = parseFloat(telemetry.burnRatePercent);

  return (
    <div className="w-full my-4 border border-neutral-200/80 dark:border-neutral-800 rounded-xl bg-white dark:bg-neutral-900 shadow-xs overflow-hidden">
      {/* Header */}
      <div className="p-4 border-b border-neutral-100 dark:border-neutral-800 flex items-center justify-between">
        <div>
          <span className="text-[11px] font-semibold uppercase tracking-wider text-neutral-500 dark:text-neutral-400">
            Swarm Treasury & FinOps
          </span>
          <h3 className="text-base font-semibold tracking-tight text-neutral-900 dark:text-neutral-50">
            Autonomous Micro-Economy
          </h3>
        </div>
        <div className="flex items-center gap-2">
          <span className="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-mono font-medium bg-neutral-100 dark:bg-neutral-800 text-neutral-700 dark:text-neutral-300">
            {telemetry.activeEscrowCount} Active Escrows
          </span>
        </div>
      </div>

      {/* Primary KPI Grid */}
      <div className="p-4 grid grid-cols-1 sm:grid-cols-3 gap-3 border-b border-neutral-100 dark:border-neutral-800">
        <div className="p-3 bg-neutral-50 dark:bg-neutral-800/40 rounded-lg border border-neutral-200/60 dark:border-neutral-800">
          <span className="text-xs text-neutral-500 dark:text-neutral-400 block mb-1">Available Liquidity</span>
          <div className="text-xl font-bold font-mono tracking-tight text-neutral-900 dark:text-neutral-50 tabular-nums">
            ${telemetry.availableBalanceUsd}
          </div>
          <span className="text-[11px] text-neutral-400 dark:text-neutral-500 mt-1 block">
            Limit: ${telemetry.totalBudgetUsd}
          </span>
        </div>

        <div className="p-3 bg-neutral-50 dark:bg-neutral-800/40 rounded-lg border border-neutral-200/60 dark:border-neutral-800">
          <span className="text-xs text-neutral-500 dark:text-neutral-400 block mb-1">Budget Burn Rate</span>
          <div className="text-xl font-bold font-mono tracking-tight text-neutral-900 dark:text-neutral-50 tabular-nums">
            {telemetry.burnRatePercent}%
          </div>
          <div className="w-full bg-neutral-200 dark:bg-neutral-700 h-1.5 rounded-full mt-2 overflow-hidden">
            <div
              className={`h-full rounded-full transition-all duration-300 ${
                burnPercentNumber > 80 ? 'bg-rose-500' : burnPercentNumber > 50 ? 'bg-amber-500' : 'bg-emerald-500'
              }`}
              style={{ width: `${Math.min(burnPercentNumber, 100)}%` }}
            />
          </div>
        </div>

        <div className="p-3 bg-neutral-50 dark:bg-neutral-800/40 rounded-lg border border-neutral-200/60 dark:border-neutral-800">
          <span className="text-xs text-neutral-500 dark:text-neutral-400 block mb-1">Safety Killswitch</span>
          <div className="text-sm font-semibold text-emerald-600 dark:text-emerald-400 flex items-center gap-1.5 mt-1">
            <div className="w-2 h-2 rounded-full bg-emerald-500 animate-pulse" />
            Active & Armed
          </div>
          <span className="text-[11px] text-neutral-400 dark:text-neutral-500 mt-1 block">
            Auto-halts on 100% budget breach
          </span>
        </div>
      </div>

      {/* Itemized Agent Spend */}
      <div className="p-4">
        <span className="text-xs font-semibold text-neutral-700 dark:text-neutral-300 block mb-2">
          Subagent Cost Allocation:
        </span>
        <div className="space-y-2">
          {agentSpendBreakdown.map((agent) => (
            <div
              key={agent.agentId}
              className="flex items-center justify-between p-2.5 rounded-lg border border-neutral-100 dark:border-neutral-800/80 bg-neutral-50/50 dark:bg-neutral-800/20 text-xs"
            >
              <div>
                <span className="font-medium text-neutral-900 dark:text-neutral-100">{agent.agentId}</span>
                <span className="text-neutral-400 dark:text-neutral-500 ml-2">({agent.role})</span>
              </div>
              <div className="flex items-center gap-3">
                <span className="text-neutral-500 dark:text-neutral-400">{agent.activeTasks} in flight</span>
                <span className="font-mono font-semibold text-neutral-900 dark:text-neutral-100 tabular-nums">
                  ${agent.spentUsd}
                </span>
              </div>
            </div>
          ))}
        </div>
      </div>
    </div>
  );
}

Sovereign Execution, Token Efficiency & Invariants

DimensionSovereign Mandate & Deterministic Contract
Frontier Model CascadeMedium / High (GPT-5.6 Sol Medium, Gemini 4 Argon, Claude Sonnet 5.5 High, Grok 4.7 High Fast)
Availability FallbackGemini 4 Argon/Pro -> Gemini 3.8 Flash; Claude Opus 5.5 -> Claude Opus 4.6 (Zero unhandled missing-model errors)
KV-Cache & Token ProtocolPin static instructions & schemas at prompt prefix (kv-cache-prefix-optimizer); pass surgical CONTEXT_MAP.md slices (<250 tokens/call) during Swarm Fan-Out
SaaT CLI & MCP DispatchCLI: vibes skill exec agentic-micro-economy-architect <audit|eval|verify|generate|blueprint> / MCP: vibes_skill_dispatch, vibes_ast_query, vibes_compile_cache, vibes_optimize_budget, vibes_verify_gate
NFR & Anti-Slop InvariantsP99 API Gateway Latency < 85ms, OpenAPI 3.1 / TypeSpec strict schema parity, RFC 9457 Problem Details error contracts, Idempotency-Key enforcement; 100% complete zero-placeholder output verified via node scripts/check-anti-slop.js --strict


Bahasa Indonesia

Direktif Eksekutif & Paradigma Ekonomi Agen (Pergeseran 2026)

Ketika agen AI otonom memanggil API berbayar, menjalankan web scraping skala besar, mengonsumsi inferensi model LLM, atau menugaskan agen lain, eksekusi tanpa kendali keuangan akan memicu kebocoran biaya komputasi yang fatal. Di era swarm software otonom, agen tidak lagi boleh beroperasi dengan akses kartu kredit perusahaan tanpa pagu ketat.

Arsitektur Ekonomi Mikro Agen mengubah swarm multi-agen menjadi sistem ekonomi mikro yang mampu meregulasi keuangannya sendiri. Setiap agen dibekali dompet kriptografis otonom, beroperasi dalam pagu anggaran (budget envelope) ketat, berpartisipasi dalam lelang tugas (reverse-auction bidding), dan bertransaksi dengan infrastruktur eksternal melalui protokol native HTTP 402 (Payment Required).


Integrasi Orkestrasi

  • Rel Kliring & Settlement: agentic-m2m-settlement, blockchain-web3-expert, formal-spec-z3-verifier.
  • Payment Gateway Fiat & Penagihan: doku-payment-gateway, doku-mcp-server, saas-billing, payment-gateway-expert.
  • FinOps AI & Kaskade Model: llm-finops-router, adaptive-model-cascade, thinking-budget-orchestrator.
  • Tata Kelola Swarm & Gerbang Critic: multi-agent-orchestration, quality-guardian, autonomous-tdd-debugger.
  • Siklus Hidup & Tata Kelola: brainstorming, zero-to-prod-orchestrator, session-memory-manager, anti-slop.

4 Pilar Utama Arsitektur Ekonomi Mikro Agen

  1. Hierarki Pagu Anggaran 3-Tingkat: Pagu Utama Swarm (Root Envelope), Batas Kecepatan Subagen (Velocity Limit), dan Brankas Escrow per Tugas.
  2. Implementasi Protokol HTTP 402: Penyedia layanan membalas kueri agen dengan kode status 402 dan invoice pembayaran mikro. Agen membayar melalui tanda tangan token kriptografis.
  3. Lelang Tugas Terbalik (Reverse-Auction Bidding): Sub-agen mengajukan penawaran harga dan durasi. Koordinator memilih kombinasi biaya-kualitas (cost-quality) terbaik.
  4. Pelepasan Dana Berdasarkan Kualitas (Critic Milestone Gate): Dana yang dikunci di escrow hanya dicairkan jika sub-agen auditor/critic menyetujui kualitas output (skor >= 0.85).

Standar Penegakan Anti-Slop

  1. Nol Pembengkakan Biaya (Zero Cost Hallucination): Jika saldo treasury utama habis, seluruh aktivitas subagen wajib berhenti seketika dan memicu notifikasi ke manusia.
  2. Keluaran Kode 100% Utuh: Middleware HTTP 402, brankas escrow atomik, dan antarmuka dashboard wajib dibuat lengkap tanpa placeholder // TODO.
  3. Verifikasi Bebas Cacat: Seluruh berkas wajib tervalidasi bersih melalui node scripts/check-anti-slop.js.

Matriks Eksekusi Berdaulat, Efisiensi Token & Invarian

DimensiMandat Berdaulat & Kontrak Deterministik
Kaskade Model FrontierMedium / High (GPT-5.6 Sol Medium, Gemini 4 Argon, Claude Sonnet 5.5 High, Grok 4.7 High Fast)
Invarian Fallback KetersediaanGemini 4 Argon/Pro -> Gemini 3.8 Flash; Claude Opus 5.5 -> Claude Opus 4.6 (Bebas gagal saat model belum tersedia/kuota penuh)
Protokol Hemat Token & KV-CacheKunci instruksi & skema statis di prefix awal (kv-cache-prefix-optimizer); kirim potongan CONTEXT_MAP.md (<250 token/panggilan) saat Fan-Out
Eksekusi SaaT CLI & MCPCLI: vibes skill exec agentic-micro-economy-architect <audit|eval|verify|generate|blueprint> / MCP: vibes_skill_dispatch, vibes_ast_query, vibes_compile_cache, vibes_optimize_budget, vibes_verify_gate
Invarian NFR & Anti-SlopLatensi P99 API < 85ms, paritas skema ketat OpenAPI 3.1 / TypeSpec, kontrak error RFC 9457 Problem Details, penegakan Idempotency-Key; kode 100% tuntas tanpa placeholder diverifikasi melalui node scripts/check-anti-slop.js --strict

Frequently asked questions

What does the Agentic Micro Economy Architect AI skill do?

M2M micro-economies, agent wallets, swarm budgets, and HTTP 402 / Ekonomi mikro M2M, dompet agen, budget swarm, dan HTTP 402.

Why use Agentic Micro Economy Architect on TypingMind?

Because you install it once and use it with any model. Agentic Micro Economy Architect is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agentic Micro Economy Architect in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/roedyrustam/vibes-plug/tree/main/skills/agentic-micro-economy-architect. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agentic Micro Economy Architect?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agentic Micro Economy Architect?

As many as you like. As long as a model supports skills, you can use Agentic Micro Economy Architect with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agentic Micro Economy Architect AI skill free?

Yes. It is published on GitHub by roedyrustam under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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