AGENTS.md Template for Payment Processing Architecture

Overview

Direct answer: This AGENTS.md template formalizes roles, handoffs, and governance for a payment processing workflow using AI coding agents, enabling reliable single-agent and multi-agent orchestration.

The AGENTS.md template describes the agent workflow, the supervisor orchestrator behavior, how context is shared, and how tools and data sources are accessed in a compliant, auditable fashion within a payment processing architecture.

When to Use This AGENTS.md Template

• Designing a payment flow that includes authorization, risk scoring, gateway interaction, settlement, and reconciliation.
• Coordinating multiple AI agents across planning, implementation, testing, and deployment.
• Establishing handoff rules and governance to prevent context drift and ensure reproducible results.
• Setting up security, auditability, and human review gates for payments and sensitive data.

Copyable AGENTS.md Template

# AGENTS.md
Project role: Payment Platform Owner
Agent roster and responsibilities:
- Planner: designs end-to-end payment flow and sequencing
- Implementer: implements steps, calls gateway and services
- Reviewer: validates outputs and compliance
- Tester: runs end-to-end tests in sandbox
- Researcher: collects signals for risk and compliance
- Domain Specialist: handles payment domain rules and regulatory considerations
Supervisor or orchestrator: OrchestratorAgent coordinates planner and implementer, enforces memory rules and tool governance
Handoff rules between agents:
- Planner to Implementer: provide context, objectives, success criteria, and required artifacts
- Implementer to Reviewer: provide deliverables, logs, and validation results
- Reviewer to Planner: provide risk assessment and approval signals
Context, memory, and source-of-truth rules:
- All decisions recorded in the central memory with references to source logs
- Source-of-truth includes gateway logs, gateway responses, and reconciliation ledger
Tool access and permission rules:
- Access only sandbox gateway for testing; secrets in vault; no hard-coded keys
- Tools limited by role; Implementer can call gateway and fraud service with restricted scopes
Architecture rules:
- Event-driven microservices; idempotent operations; traceable IDs
- Strict boundary between payment core and domain logic
File structure rules:
- Keep all workflow context under payments/ and separate agents under payments/ai-skills/agents-md-templates/
Data, API, or integration rules when relevant:
- Use idempotent payment requests; record all external calls
- Respect data minimization and PCI-DSS considerations
Validation rules:
- Validate currency, amount, merchant, and recipient on input
- Validate gateway response codes and settlement confirmations
Security rules:
- Never log sensitive data; rotate keys; use vault for secrets
- Enforce least privilege and role-based access
Testing rules:
- Unit tests for each agent; integration tests with sandbox gateway; end-to-end tests in staging
Deployment rules:
- CI/CD with feature flags; canary deployment for payment services
Human review and escalation rules:
- High-risk or failed payments require human review before final settlement
Failure handling and rollback rules:
- On failure, retry with backoff; if persistent, rollback to previous good state
Things Agents must not do:
- Do not bypass governance; do not expose secrets; do not mutate live production data without approval

Recommended Agent Operating Model

Roles and decision boundaries: Planner defines the workflow; Implementer executes and gathers evidence; Reviewer validates; Tester confirms; Researcher finds signals; Domain Specialist enforces domain rules. The Orchestrator coordinates, ensures memory integrity, and enforces tool governance. Escalation paths: if risk is elevated or a failure cannot be resolved, escalate to domain specialist and (if needed) human reviewer.

Recommended Project Structure

payments/
  orchestrator/
  agents/
    planner/
    implementer/
    reviewer/
    tester/
    researcher/
    domain-specialist/
  integrations/
  data/
  tests/
  deployments/

Core Operating Principles

• Clear, auditable decisions with traceable memory
• Idempotent operations and deterministic outputs
• Explicit handoffs and escalation paths
• Strong tool governance and secrets management
• Domain-informed decision boundaries

Agent Handoff and Collaboration Rules

• Planner to Implementer: supply context, success criteria, and artifacts
• Implementer to Reviewer: provide logs and validation results
• Reviewer to Planner: provide risk assessment and approval
• Researcher and Domain Specialist provide signals as needed

Tool Governance and Permission Rules

• Devices: gateway sandbox; vault for secrets; limit to necessary scopes
• API calls: strict rate limits; idempotent keys; no production keys in agent memory
• Approval gates: automated checks plus human review for high-risk actions

Code Construction Rules

• Write modular, testable agents; avoid hard-coded values
• Use idempotent operations; deterministic outcomes
• Keep logs structured and searchable

Security and Production Rules

• Secrets in vault; rotate keys; monitor for leakage
• Production changes require governance and approvals
• Payments must be auditable with immutable logs

Testing Checklist

• Unit tests for each agent
• Integration tests with sandbox gateway
• End-to-end tests in staging
• Security and regression tests

Common Mistakes to Avoid

• Skipping memory/context sharing leading to drift
• Bypassing tool governance or secrets management
• Unbounded escalation without clear criteria
• Producing non-idempotent operations

Related implementation resources: AI Use Case for Corporate Event Managers Using Slack To Orchestrate Day-Of Venue Tasks Across Multi-Department Teams and AI Agent Use Case for Wholesalers Using Multi-Currency Ledger Trackers To Calculate Foreign Exchange Risk Exposure Across Global Accounts.

FAQ

What is the purpose of this AGENTS.md Template for payment processing architecture?

To provide a complete operating manual for AI coding agents coordinating end-to-end payments with governance and handoffs.

How does multi-agent orchestration handle gateway failures?

The orchestrator retries with idempotent keys, flags high-risk issues for human review, and may route to fallback payment methods.

What constitutes a proper handoff between Planner and Implementer?

Context, objectives, success criteria, and artifacts plus confirmation signals from Implementer.

How are secrets and API keys managed?

Secrets live in a vault; keys rotated; access scoped per workflow; never hard-coded.

How is auditing and human review integrated?

Critical decisions are logged and subject to human review; audits stored in an immutable ledger.