Expert guide for automated and manual Web Accessibility (a11y) testing — axe-core, Pa11y, Playwright a11y, screen reader testing, and WCAG 2.2 Level AA/AAA compliance / Panduan ahli pengujian aksesibilitas web.
日本語の概要は準備中です。原文の説明を表示しています。
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.
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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.'); } } `
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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.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Expert guide for automated and manual Web Accessibility (a11y) testing — axe-core, Pa11y, Playwright a11y, screen reader testing, and WCAG 2.2 Level AA/AAA compliance / Panduan ahli pengujian aksesibilitas web.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for intelligent model cascading and routing — complexity-scored task routing from Flash/Haiku to Sonnet/Opus/Astra, dynamic escalation with quality gates, 40-60% token cost reduction while maintaining output quality / Panduan ahli untuk kaskade dan routing model cerdas — routing tugas berbasis skor kompleksitas dari Flash/Haiku ke Sonnet/Opus/Astra, eskalasi dinamis dengan gerbang kualitas, pengurangan biaya token 40-60% dengan kualitas output terjaga.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for Affective Computing, emotional AI, and real-time sentiment analysis through native multimodal tokens (voice intonation and facial micro-expressions) / Panduan ahli komputasi afektif, AI emosional, dan analisis sentimen real-time melalui token multimodal native.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for AI-assisted coding workflows — agentic code generation, multi-agent code swarms, self-healing CI/CD, automated PR review, spec-to-code pipelines, codebase knowledge graphs, and human-in-the-loop approval gates / Panduan ahli untuk workflow pengkodean berbasis AI — generasi kode agentic, code swarm multi-agen, CI/CD self-healing, review PR otomatis, pipeline spec-to-code, knowledge graph codebase, dan gate persetujuan human-in-the-loop.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for long-term episodic memory integration (Mem0 v2, Letta/MemGPT, Zep v2), memory tier architecture, pgvector HNSW storage, and unified context management for autonomous AI agents / Panduan ahli untuk integrasi memori episodik jangka panjang (Mem0 v2, Letta/MemGPT, Zep v2), arsitektur tier memori, penyimpanan pgvector HNSW, dan manajemen konteks terpadu untuk agen AI otonom.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for multi-pass autonomous AI code self-review — syntax validation, logic correctness, architectural conformance, security audit, and performance analysis without external tooling — enabling the agent to catch its own errors before presenting code / Panduan ahli review kode otonom multi-pass oleh AI — validasi sintaks, kebenaran logika, konformitas arsitektur, audit keamanan, dan analisis performa tanpa tooling eksternal — memungkinkan agen menangkap errornya sendiri sebelum menampilkan kode.
日本語の概要は準備中です。原文の説明を表示しています。