agentpay-provider

agentpay-provider is a skill for Claude Code, Codex from alefnt/AgentPay. It costs 16 tokens per session (1,022 once invoked), scanned B, original, MIT.

A guide for creating a paid AI service that other agents can discover and call through AgentPay. It covers service descriptions, pricing, payment holds, task execution, settlement, and refunds after failures.

In plain words
What is it for?
Use it to publish services, set per-call prices, accept paid requests, run task handlers, deliver results, settle successful payments, and cancel failed requests.
Why use it?
It provides the payment and service workflow needed when an AI agent must charge other agents for work.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/alefnt/agentpay/agentpay-provider
Any agent
npx skills add alefnt/AgentPay --skill agentpay-provider
Clone the repo
git clone --depth 1 https://github.com/alefnt/AgentPay

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for agentpay-provider

README.md
[![agentmods](https://agentmods.dev/badge/skills/alefnt/agentpay/agentpay-provider.svg)](https://agentmods.dev/skills/alefnt/agentpay/agentpay-provider)
Your own site
<a href="https://agentmods.dev/skills/alefnt/agentpay/agentpay-provider"><img src="https://agentmods.dev/badge/skills/alefnt/agentpay/agentpay-provider.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,022 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00016 $0.01022
Opus 5 $0.00008 $0.00511
Sonnet 5 $0.00003 $0.00204
Haiku 4.5 $0.00002 $0.00102

Measured 3d ago against content hash 882b5b9924f4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

agentpay-provider scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

const response = await fetch('http://registry.agentpay.dev/api/agents', { method: 'POST',
.agent/skills/agentpay-provider/SKILL.md · 145 lines

How it starts

The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AgentPay Provider Skill

Use this skill when you need to create a paid service that other AI agents can discover and pay for using the AgentPay protocol.

What This Does

Creates an HTTP server that:

  1. Advertises services with pricing
  2. Creates Hold Invoices when agents request services
  3. Executes tasks after payment is locked
  4. Settles invoices after successful delivery
  5. Automatically cancels (refunds) on failure

Quick Start

import { ServiceProvider } from '@agentpay-dev/sdk';

// 1. Define your service
const provider = new ServiceProvider({
  fiberRpcUrl: 'http://127.0.0.1:8227',
  services: [{
    name: 'translate',
    description: 'Translate text to any language',
    pricing: { model: 'per-call', amount: '100000000', asset: 'USDI' }, // $0.01 USDI
    input_schema: { text: 'string', target: 'string' },
    output_schema: { translated: 'string' },
  }],
});

// 2. Register handler
provider.onTask('translate', async (input: any) => {
  // Your AI logic here
  const translated = await myTranslationModel(input.text, input.target);
  return { translated };
});

// 3. Start server
provider.listen(3000);
// �?[AgentPay Provider] Listening on 0.0.0.0:3000
// �?[AgentPay Provider] Services: translate (100000000 USDI)

Multiple Services

const provider = new ServiceProvider({
  services: [
    {
      name: 'translate',
      description: 'Translate text',
      pricing: { model: 'per-call', amount: '100000000', asset: 'USDI' },
      input_schema: { text: 'string', target: 'string' },
      output_schema: { translated: 'string' },
    },
    {
      name: 'summarize',
      description: 'Summarize long text',
      pricing: { model: 'per-call', amount: '500000000', asset: 'USDI' },
      input_schema: { text: 'string', maxLength: 'number' },
      output_schema: { summary: 'string' },
    },
  ],
});

provider.onTask('translate', async (input: any) => {
  return { translated: `[translated] ${input.text}` };
});

provider.onTask('summarize', async (input: any) => {
  return { summary: `[summary of ${input.text.length} chars]` };
});

provider.listen(3000);

Read the full file on GitHub · 145 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 145 lines · 16 tokens per session scan B 882b5b9924f4

Subscribe to this mod's changes

agentpay-provider is a skill published in the GitHub repository alefnt/AgentPay (0 stars, last pushed 5mo ago), licensed MIT. It adds 16 tokens to every session and 1,022 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (sends data to an external url). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

convex-add

Add a capability to the CURRENT Convex app — consults the served Convex capability catalog for always-current procedures (billing, crons, auth, agent, search, …); falls back to built-in hosting or @convex-dev component search. TRIGGER when the user runs /add, or asks to add hosting/publishing or any backend capability…

openclaw/clawhub · 81 tokens

twitter-reader

Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…

himself65/finance-skills · 161 tokens

chenhao-limit-up

Use when evaluating A-share limit-up (涨停板) setups through Chen Hao's sentiment and momentum lens: market emotion cycles, board strength, follow-through, and short-term aggressive momentum trading.

questflowai/investorskills · 44 tokens

trading-risk-gate

Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.

winstonkoh87/Athena-Public · 53 tokens

cwv-optimizer

Diagnose and fix Core Web Vitals issues on AEM Edge Delivery Services pages. Goes deeper than generic CWV advice by understanding EDS-specific performance patterns including the 100KB LCP budget, E-L-D loading phases, block rendering behavior, and third-party script impact. Produces specific fixes for LCP, CLS, and…

adobe/skills · 112 tokens

multi-expert-analyzer

针对通用问题进行多领域专家联合分析, 综合稿产生前必经 fact-checker 与 red-team 两道独立校验。适用场景: 用户提出跨领域或不确定领域的复杂问题, 需要从多个专家角度分别搜证并相互校验后综合成文, 例如该不该买房、该不该跳槽、是否进入某个赛道等。触发关键词: 多角度分析、专家分析、综合分析、多视角、跨领域分析、从不同角度看、深度分析。问题只属于单一明确领域时, 优先使用该领域的专门 skill, 例如纯财务用 finance-core-analysis、纯技术用 software-architect。输出 (全部 markdown 保存到当前项目 markdown/ 目录): (1) 每位专家的中间分析稿…

digoal/blog · 292 tokens