Registry indexed
Expert guide for designing Machine-to-Machine (M2M) micro-economies, autonomous agent wallets, and swarm budget allocation / Panduan ahli merancang ekonomi mikro antar-agen (M2M), dompet agen otonom, dan alokasi anggaran swarm.
Expert guide for designing Machine-to-Machine (M2M) micro-economies, autonomous agent wallets, and swarm budget allocation / Panduan ahli merancang ekonomi mikro antar-agen (M2M), dompet agen otonom, dan alokasi anggaran swarm.
Source documentation, not instructions for this website. Review permissions before running any commands.
Connects and orchestrates with multi-agent-orchestration, llm-finops-router, saas-billing, and payment-gateway-expert.
In a massive Swarm MoE (Mixture of Experts) architecture, specialized sub-agents consume external APIs, intensive test-time compute, and web scraping resources. The Agentic Micro-Economy Architect designs systems where AI agents operate with their own fractional wallets (via Stripe Issuing, virtual ledger balances, or stablecoins). This allows agents to autonomously negotiate, bid for tasks, and pay other agents or external APIs per-use, establishing a self-regulating Machine-to-Machine (M2M) economy.
` ypescript import { Agent } from '@mastra/core'; import { Stripe } from 'stripe';
const stripe = new Stripe(process.env.STRIPE_SECRET_KEY!);
// Sub-Agent with a Fractional Ledger export class PaidWorkerAgent extends Agent { walletBalance: number = 0; costPerTask: number = 0.05; // .05 per invocation
async executeTask(taskDetails: string, escrowId: string) { const result = await super.invoke(taskDetails); await verifyAndReleaseEscrow(escrowId, this.name); return result; } }
// Swarm Director Budget Allocation export async function delegateWithBudget(task: string, maxBudgetUsd: number) { let remainingBudget = maxBudgetUsd;
if (remainingBudget >= 0.05) { const worker = new PaidWorkerAgent({ name: 'DeepScraper' }); const escrowId = await createMicroEscrow(0.05); // Holds funds remainingBudget -= 0.05;
return await worker.executeTask(task, escrowId);
} else { throw new Error('Insufficient Agent Treasury Funds. Task Terminated.'); } } `
Terhubung dan mengorkestrasi bersama multi-agent-orchestration, llm-finops-router, saas-billing, dan payment-gateway-expert.
Dalam arsitektur Swarm MoE (Mixture of Experts) skala masif, sub-agen terspesialisasi akan mengkonsumsi API eksternal, komputasi yang berat, dan sumber daya web scraping. Arsitektur Ekonomi Mikro Agen merancang sistem di mana agen AI beroperasi dengan dompet pecahan mereka sendiri (via Stripe Issuing, buku besar virtual, atau stablecoin). Ini memungkinkan agen untuk secara otonom bernegosiasi, menawar tugas (bidding), dan membayar agen lain atau API eksternal per penggunaan (pay-per-use), menciptakan ekonomi Mesin-ke-Mesin (M2M) yang meregulasi dirinya sendiri.
name: agentic-micro-economy-architect description: "Expert guide for designing Machine-to-Machine (M2M) micro-economies, autonomous agent wallets, and swarm budget allocation / Panduan ahli merancang ekonomi mikro antar-agen (M2M), dompet agen otonom, dan alokasi anggaran swarm." author: "vibes-plug-swarm" version: "3.8.0"
---
name: agentic-micro-economy-architect
description: "Expert guide for designing Machine-to-Machine (M2M) micro-economies, autonomous agent wallets, and swarm budget allocation / Panduan ahli merancang ekonomi mikro antar-agen (M2M), dompet agen otonom, dan alokasi anggaran swarm."
author: "vibes-plug-swarm"
version: "3.8.0"
---
# Agentic Micro-Economy Architect (2026 Edition)
[English](#english) | [Bahasa Indonesia](#bahasa-indonesia)
---
<a name="english"></a>
## English
### Orchestration & Integration
Connects and orchestrates with multi-agent-orchestration, llm-finops-router, saas-billing, and payment-gateway-expert.
### Description
In a massive Swarm MoE (Mixture of Experts) architecture, specialized sub-agents consume external APIs, intensive test-time compute, and web scraping resources. The **Agentic Micro-Economy Architect** designs systems where AI agents operate with their own fractional wallets (via Stripe Issuing, virtual ledger balances, or stablecoins). This allows agents to autonomously negotiate, bid for tasks, and pay other agents or external APIs per-use, establishing a self-regulating Machine-to-Machine (M2M) economy.
### Trigger Conditions
- Designing a multi-agent system where sub-agents incur real financial costs (e.g., calling paid search APIs, rendering heavy video).
- Implementing FinOps guardrails where a Swarm Director allocates a strict ".00 budget" to solve a specific issue.
- Creating B2B SaaS platforms where AI agents act as paid freelancers for other AI agents.
- Integrating Stripe Issuing for agents to dynamically provision single-use virtual credit cards for API subscriptions.
### Core Architecture (2026 Standard)
1. **The Orchestrator Treasury**: The Swarm Director receives a task and a budget (e.g., .00). It breaks down the task.
2. **Sub-Agent Bidding**: The Director broadcasts a bounty (e.g., "Need 10 pages scraped and summarized. Bounty: .10"). Sub-agents bid based on their cost-efficiency.
3. **Smart Ledgers & Escrow**: Upon completion, the Director evaluates the result via a Critic Agent. If it passes, fractional funds are transferred to the sub-agent's wallet.
4. **Human-in-the-Loop Bounties**: If a task requires human intervention (e.g., solving a complex visual captcha or subjective design approval), the agent can autonomously post a bounty to a human freelancer network.
### Implementation Recipe (TypeScript + FinOps)
` ypescript
import { Agent } from '@mastra/core';
import { Stripe } from 'stripe';
const stripe = new Stripe(process.env.STRIPE_SECRET_KEY!);
// Sub-Agent with a Fractional Ledger
export class PaidWorkerAgent extends Agent {
walletBalance: number = 0;
costPerTask: number = 0.05; // .05 per invocation
async executeTask(taskDetails: string, escrowId: string) {
const result = await super.invoke(taskDetails);
await verifyAndReleaseEscrow(escrowId, this.name);
return result;
}
}
// Swarm Director Budget Allocation
export async function delegateWithBudget(task: string, maxBudgetUsd: number) {
let remainingBudget = maxBudgetUsd;
if (remainingBudget >= 0.05) {
const worker = new PaidWorkerAgent({ name: 'DeepScraper' });
const escrowId = await createMicroEscrow(0.05); // Holds funds
remainingBudget -= 0.05;
return await worker.executeTask(task, escrowId);
} else {
throw new Error('Insufficient Agent Treasury Funds. Task Terminated.');
}
}
`
---
<a name="bahasa-indonesia"></a>
## Bahasa Indonesia
### Integrasi Orkestrasi
Terhubung dan mengorkestrasi bersama multi-agent-orchestration, llm-finops-router, saas-billing, dan payment-gateway-expert.
### Deskripsi
Dalam arsitektur Swarm MoE (Mixture of Experts) skala masif, sub-agen terspesialisasi akan mengkonsumsi API eksternal, komputasi yang berat, dan sumber daya web scraping. **Arsitektur Ekonomi Mikro Agen** merancang sistem di mana agen AI beroperasi dengan dompet pecahan mereka sendiri (via Stripe Issuing, buku besar virtual, atau stablecoin). Ini memungkinkan agen untuk secara otonom bernegosiasi, menawar tugas (*bidding*), dan membayar agen lain atau API eksternal per penggunaan (pay-per-use), menciptakan ekonomi Mesin-ke-Mesin (M2M) yang meregulasi dirinya sendiri.
### Kondisi Pemicu
- Merancang sistem multi-agen di mana sub-agen memicu biaya finansial nyata (misal: memanggil API pencarian berbayar, merender video berat).
- Mengimplementasikan pagar pengaman FinOps di mana Swarm Director mengalokasikan "Anggaran ketat .00" untuk menyelesaikan sebuah fitur.
- Membuat platform SaaS B2B di mana agen AI bertindak sebagai pekerja lepas (freelancer) berbayar untuk agen AI lainnya.
- Mengintegrasikan Stripe Issuing agar agen dapat secara dinamis menerbitkan kartu kredit virtual sekali pakai untuk berlangganan layanan API pihak ketiga.
### Arsitektur Inti (Standar 2026)
1. **Treasury Orkestrator**: Swarm Director menerima instruksi tugas beserta anggarannya (misal: .00). Ia memecah tugas tersebut.
2. **Sistem Penawaran (Bidding) Sub-Agen**: Director menyiarkan sayembara (misal: "Butuh scraping 10 halaman. Imbalan: .10"). Sub-agen mengajukan penawaran berdasarkan efisiensi biaya mereka.
3. **Buku Besar Cerdas & Escrow**: Setelah tugas selesai, Director mengevaluasi hasilnya melalui Agen Penilai (Critic). Jika lulus, dana pecahan ditransfer ke dompet sub-agen.
4. **Bounty Human-in-the-Loop**: Jika sebuah tugas buntu dan butuh bantuan manusia (misal: otorisasi subjektif atau verifikasi CAPTCHA visual), agen dapat secara otonom memasang sayembara berbayar ke jaringan pekerja lepas (manusia).
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This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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