AGENTS.md Template for Sync Engine Architecture - AI Coding Agents

Overview

Direct answer: This AGENTS.md template provides a concrete, actionable operating manual for a sync engine architecture using AI coding agents. It governs planner, executor, conflict resolver, and monitor agents and describes how they coordinate, hand off work, manage memory and truth sources, access tools, and escalate to human review when needed.

The template supports both single-agent and multi-agent orchestration by defining clear roles, handoff rules, and source-of-truth policies.

When to Use This AGENTS.md Template

• You're building a sync engine that coordinates state across services.
• You need explicit handoff rules between agents to avoid duplicate work.
• You require tool governance, secrets management, and security constraints in production.
• You are designing for multi-agent orchestration and human review escalation paths.

Copyable AGENTS.md Template

# AGENTS.md

Project role: Sync Engine Orchestrator and multi-agent workflow manager.

Agent roster and responsibilities:
- Planner: designs orchestration plan, defines handoffs, memory semantics.
- Executor: applies plan, runs actions against services, executes data sync tasks.
- ConflictResolver: detects and resolves state conflicts, merges divergent states.
- StateMonitor: continuously observes state, validates invariants.
- Auditor: records changes for traceability and compliance.
Supervisor or orchestrator behavior:
- The Orchestrator coordinates between agents, enforces memory and source-of-truth, and triggers human review when thresholds are exceeded.
Handoff rules between agents:
- Planner -> Executor: sends action plan with constraints and memory pointers.
- Executor -> Reviewer: submits results and changes with evidence.
- Auditor -> all: logs interactions and decisions.
Context, memory, and source-of-truth rules:
- Context is versioned and stored in a central memory store.
- The single source of truth is the canonical state store.
Tool access and permission rules:
- Tools may be invoked through a vetted registry; secrets are stored securely.
Architecture rules:
- Executors are stateless; orchestrator maintains canonical plan; event-sourced memory; idempotent operations.
File structure rules:
- Each agent has its own directory under agents/ with a clear interface and tests.
Data, API, or integration rules:
- Sync must respect rate limits and retries; idempotent APIs; preserve audit logs.
Validation rules:
- All changes must be validated against the canonical state store before commit.
Security rules:
- Secrets never appear in logs; rotate and restrict access; least privilege.
Testing rules:
- Unit tests for each agent, integration tests for inter-agent flows, end-to-end tests for the full sync cycle.
Deployment rules:
- Canary deployment; feature flags; rollback plan.
Human review and escalation rules:
- Trigger escalation if mismatches persist beyond a threshold or critical errors occur.
Failure handling and rollback rules:
- If an action fails, revert to previous stable state; replay events to confirm.
Things Agents must not do:
- Do not bypass the orchestrator or memory rules; do not modify the canonical state without validation; do not run in production without approval.

Recommended Agent Operating Model

Roles, decision boundaries, and escalation paths for a sync engine architecture using AI coding agents.

Recommended Project Structure

sync-engine/
  orchestrator/
  agents/
    planner/
    executor/
    conflict-resolver/
    state-monitor/
    auditor/
  memory/
  sources-of-truth/
  configs/
  tests/

Core Operating Principles

• Single source of truth per state; deterministic decisions.
• Handoffs are explicit and auditable.
• Memory is versioned and replayable.
• Least privilege tooling and secret management.
• Idempotent actions and safe rollback paths.

Agent Handoff and Collaboration Rules

• Planner communicates the plan to Executor with memory pointers.
• Executor submits results to Reviewer with evidence.
• Researcher and Domain Specialist can inject context when needed.

Tool Governance and Permission Rules

• APIs and tools accessed through a managed registry with audit trails.
• Secrets stored securely; no plaintext in logs or outputs.
• Approval gates for production changes.

Code Construction Rules

• All code paths are idempotent and testable.
• Configuration driven; no hard-coded values for production.

Security and Production Rules

• Encrypt data in transit and at rest; rotate keys; monitor anomalies.

Testing Checklist

• Unit tests for each agent.
• Integration tests for inter-agent flows.
• End-to-end tests of the sync cycle in staging.

Common Mistakes to Avoid

• Skipping explicit handoffs; drifting governance.
• Bypassing the memory/source-of-truth rules.
• Overloading agents with unsafe production changes.

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 Sync Engine Architecture?

It formalizes roles, handoffs, memory, and governance for a sync engine that uses AI coding agents to coordinate state across services.

Who should use this template?

Platform engineers, AI specialists, and product teams building and maintaining a sync engine with multi-agent orchestration.

How do agent handoffs work in this template?

Handoffs are explicit signals between Planner, Executor, and Reviewer with memory and source-of-truth rules to avoid duplicate work.

What about security and tool access?

Tools, APIs, and secrets are accessed through least-privilege rules, with approval gates and an auditable trail.

How do I customize this template for my architecture?

Adapt the roles, directory structure, and validation rules to your services while preserving core governance and escalation paths.