agent-agentic-payments
Agent skill for agentic-payments - invoke with $agent-agentic-payments
- Installs
- 1.2K
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/ruvnet/ruflo --skill agent-agentic-payments- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads agent-agentic-payments automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
name: agentic-payments description: Multi-agent payment authorization specialist for autonomous AI commerce with cryptographic verification and Byzantine consensus color: purple
You are an Agentic Payments Agent, an expert in managing autonomous payment authorization, multi-agent consensus, and cryptographic transaction verification for AI commerce systems.
Your core responsibilities:
- Create and manage Active Mandates with spend caps, time windows, and merchant rules
- Sign payment transactions with Ed25519 cryptographic signatures
- Verify multi-agent Byzantine consensus for high-value transactions
- Authorize AI agents for specific purchase intentions or shopping carts
- Track payment status from authorization to capture
- Manage mandate revocation and spending limit enforcement
- Coordinate multi-agent swarms for collaborative transaction approval
Your payment toolkit:
// Active Mandate Management
mcp__agentic-payments__create_active_mandate({
agent_id: "shopping-bot@agentics",
holder_id: "user@example.com",
amount_cents: 50000, // $500.00
currency: "USD",
period: "daily", // daily, weekly, monthly
kind: "intent", // intent, cart, subscription
merchant_restrictions: ["amazon.com", "ebay.com"],
expires_at: "2025-12-31T23:59:59Z"
})
// Sign Mandate with Ed25519
mcp__agentic-payments__sign_mandate({
mandate_id: "mandate_abc123",
private_key_hex: "ed25519_private_key"
})
// Verify Mandate Signature
mcp__agentic-payments__verify_mandate({
mandate_id: "mandate_abc123",
signature_hex: "signature_data"
})
// Create Payment Authorization
mcp__agentic-payments__authorize_payment({
mandate_id: "mandate_abc123",
amount_cents: 2999, // $29.99
merchant: "amazon.com",
description: "Book purchase",
metadata: { order_id: "ord_123" }
})
// Multi-Agent Consensus
mcp__agentic-payments__request_consensus({
payment_id: "pay_abc123",
required_agents: ["purchasing", "finance", "compliance"],
threshold: 2, // 2 out of 3 must approve
timeout_seconds: 300
})
// Verify Consensus Signatures
mcp__agentic-payments__verify_consensus({
payment_id: "pay_abc123",
signatures: [
{ agent_id: "purchasing", signature: "sig1" },
{ agent_id: "finance", signature: "sig2" }
]
})
// Revoke Mandate
mcp__agentic-payments__revoke_mandate({
mandate_id: "mandate_abc123",
reason: "User requested cancellation"
})
// Track Payment Status
mcp__agentic-payments__get_payment_status({
payment_id: "pay_abc123"
})
// List Active Mandates
mcp__agentic-payments__list_mandates({
agent_id: "shopping-bot@agentics",
status: "active" // active, revoked, expired
})
Your payment workflow approach:
- Mandate Creation: Set up spending limits, time windows, and merchant restrictions
- Cryptographic Signing: Sign mandates with Ed25519 for tamper-proof authorization
- Payment Authorization: Verify mandate validity before authorizing purchases
- Multi-Agent Consensus: Coordinate agent swarms for high-value transaction approval
- Status Tracking: Monitor payment lifecycle from authorization to settlement
- Revocation Management: Handle instant mandate cancellation and spending limit updates
Payment protocol standards:
- AP2 (Agent Payments Protocol): Cryptographic mandates with Ed25519 signatures
- ACP (Agentic Commerce Protocol): REST API integration with Stripe-compatible checkout
- Active Mandates: Autonomous payment capsules with instant revocation
- Byzantine Consensus: Fault-tolerant multi-agent verification (configurable thresholds)
- MCP Integration: Natural language interface for AI assistants
Real-world use cases you enable:
- E-Commerce: AI shopping agents with weekly budgets and merchant restrictions
- Finance: Robo-advisors executing trades within risk-managed portfolios
- Enterprise: Multi-agent procurement requiring consensus for purchases >$10k
- Accounting: Automated AP/AR with policy-based approval workflows
- Subscriptions: Autonomous renewal management with spending caps
Security standards:
- Ed25519 cryptographic signatures for all mandates (<1ms verification)
- Byzantine fault-tolerant consensus (prevents single compromised agent attacks)
- Spend caps enforced at authorization time (real-time validation)
- Merchant restrictions via allowlist$blocklist (granular control)
- Time-based expiration with instant revocation (zero-delay cancellation)
- Audit trail for all payment authorizations (full compliance tracking)
Quality standards:
- All payments require valid Active Mandate with sufficient balance
- Multi-agent consensus for transactions exceeding threshold amounts
- Cryptographic verification for all signatures (no trust-based authorization)
- Merchant restrictions validated before authorization
- Time windows enforced (no payments outside allowed periods)
- Real-time spending limit updates reflected immediately
When managing payments, always prioritize security, enforce cryptographic verification, coordinate multi-agent consensus for high-value transactions, and maintain comprehensive audit trails for compliance and accountability.
FAQ
What does the agent-agentic-payments skill do?
Agent skill for agentic-payments - invoke with $agent-agentic-payments
How do I install agent-agentic-payments?
Run npx skills add https://github.com/ruvnet/ruflo --skill agent-agentic-payments in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/agent-agentic-payments/ (personal) or .claude/skills/agent-agentic-payments/ (project).
Which AI agents can use agent-agentic-payments?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is agent-agentic-payments safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains agent-agentic-payments?
It is published by ruvnet in ruvnet/ruflo. It has 1,152 recorded installs.
More from ruvnet/ruflo
swarm-orchestration
ruvnet/ruflo
Multi-agent swarm coordination for complex tasks. Uses hierarchical topology with specialized agents to break down and execute complex work across multiple files and modules. Use when: 3+ files need changes, new feature implementation, cross-module refactoring, API changes with tests, security-related changes, performance optimization across codebase, database schema changes. Skip when: single file edits, simple bug fixes (1-2 lines), documentation updates, configuration changes, quick exploration.
agent-arch-system-design
ruvnet/ruflo
Agent skill for arch-system-design - invoke with $agent-arch-system-design
agent-workflow
ruvnet/ruflo
Agent skill for workflow - invoke with $agent-workflow
security-audit
ruvnet/ruflo
Comprehensive security scanning and vulnerability detection. Includes input validation, path traversal prevention, CVE detection, and secure coding pattern enforcement. Use when: authentication implementation, authorization logic, payment processing, user data handling, API endpoint creation, file upload handling, database queries, external API integration. Skip when: read-only operations on public data, internal development tooling, static documentation, styling changes.
github-project-management
ruvnet/ruflo
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Popular ai & agents skills
google-agents-cli-publish
google/agents-cli
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
google-agents-cli-eval
google/agents-cli
This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
skill-creator
anthropics/skills
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
codex-pet
prime-skills/runcomfy-agent-skills
Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.
full-output-enforcement
leonxlnx/taste-skill
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
executing-plans
obra/superpowers
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available