AGENTS.md Template for Real-Time Collaboration Systems

Overview

Direct answer: The AGENTS.md Template for Real-Time Collaboration Systems provides a formal operating manual that governs the real-time AI coding agent workflow and multi-agent orchestration. It defines roles handoffs memory tool governance and escalation rules to enable predictable collaboration in live environments.

When to Use This AGENTS.md Template

Establish a repeatable operating model for real-time collaboration systems with AI coding agents
Coordinate planner implementer tester reviewer researchers and domain specialists across live sessions
Document memory rules source of truth and data flow for auditability and compliance
Provide a governance framework for tool access secrets and production safety

Copyable AGENTS.md Template

Copy this AGENTS.md template block into your repository to define the real time collaboration workflow across agents.

# AGENTS.md
Project role: Real-Time Collaboration Agent System
Agent roster and responsibilities:
- Planner: defines goals sequencing dependencies and handoffs
- Implementer: executes actions from planner interacts with data streams
- Reviewer: validates outputs ensures policy compliance and quality
- Tester: runs experiments tests integrations and performance
- Researcher: fetches data context telemetry and insights
- Domain Specialist: enforces domain constraints and domain-specific checks
Supervisor or orchestrator behavior:
- Orchestrates agent execution monitors outputs enforces memory state and triggers handoffs
- Maintains a single source of truth per session, log all decisions
Handoff rules between agents:
- Planner -> Implementer: provide goals data context and required actions
- Implementer -> Reviewer: deliver results and validations
- Researcher -> Planner: supply new data and insights
Context memory and source-of-truth rules:
- All agents read from and write to a session memory store
- session_id is the primary key for the source of truth
Tool access and permission rules:
- Tools: real-time data stream API storage authentication service
- Access: least privilege per role; secrets in a vault
Architecture rules:
- Event-driven microservices with stateless agents
- State changes persisted via versioned events
File structure rules:
- Use a minimal folder structure focused on the workflow
- Avoid duplicating logic across agents
Data API or integration rules:
- All API calls authenticated and auditable
- Data shaped and validated against shared schemas
Validation rules:
- Validate events against schema
- Idempotent operations
Security rules:
- Secrets never logged; rotate regularly
- Enforce least privilege and secret management
Testing rules:
- Unit tests per agent
- Integration tests across agent handoffs
- End-to-end tests for real-time synchronization
Deployment rules:
- CI/CD with feature flags and canary deployments
- Rollback plan for production issues
Human review and escalation rules:
- Critical decisions require human review
- On-call escalation if blockers persist
Failure handling and rollback rules:
- If an agent fails, revert to last good state and retry with backoff
- Maintain an audit trail of failures
Things Agents must not do:
- Do not bypass approvals or safety checks
- Do not mutate historical decisions outside approved paths

Recommended Agent Operating Model

Roles and responsibilities are clearly bounded with escalation paths. The planner negotiates goals while the implementer executes actions with telemetry feedback. Reviewers provide compliance checks testers ensure integration quality researchers supply data context and domain specialists enforce domain constraints. Escalation flows go to the orchestrator first and to humans if blockers persist.

Recommended Project Structure

Use this workflow specific directory tree.

real_time_collab/
├── agents/
│   ├── planner/
│   ├── implementer/
│   ├── reviewer/
│   ├── tester/
│   ├── researcher/
│   └── domain_specialist/
├── workflows/
│   └── real_time_collab/
├── data/
├── services/
├── docs/
└── tests/

Core Operating Principles

Single source of truth per session
Deterministic decision boundaries with explicit handoffs
Least privilege and auditable actions
Idempotent operations and robust error handling
Observability across all agents and memory state

Agent Handoff and Collaboration Rules

Planner coordinates goals and handoff points with Implementer
Implementer passes results to Reviewer and shares context with Tester
Researcher feeds data to Planner and Domain Specialist for validation
Domain Specialist enforces domain constraints across all steps

Tool Governance and Permission Rules

Commands and API calls require explicit approval gates
Edits to shared artifacts restricted by role and audited
Secrets stored securely and not logged
Access to production systems restricted and revocable
All external service calls are logged and rate-limited
Handoff and deployment gates require supervisor confirmation

Code Construction Rules

Code generated by agents is versioned and traceable
Functions are small and composable for testability
Input validation is mandatory for all data streams
All changes are reviewed before production

Security and Production Rules

Secrets rotate and are never logged
RBAC enforced for all tools and services
Production changes require formal approvals and canary tests

Testing Checklist

Unit tests for each agent
Integration tests for handoffs
End-to-end tests for real-time sync
Performance tests under load

Common Mistakes to Avoid

Skipping memory discipline and source of truth
Unclear handoffs leading to context drift
Violating least privilege in tool access
Overcomplex orchestration without failure handling

FAQ

What is the AGENTS.md Template for Real-Time Collaboration?

The AGENTS.md Template provides a formal operating manual that governs real-time collaboration agent workflows, enabling multi-agent orchestration, handoffs, and governance.

How does this template support multi-agent orchestration?

It defines agent roles, responsibilities, memory and source of truth rules, and clear handoff points between planner implementer reviewer tester and domain specialists.

What are the handoff rules between agents?

Handoffs are defined with data context and goals ensuring continuity of work and traceability of decisions.

How is memory and source-of-truth maintained?

A centralized session memory per collaboration versioned events and a single source of truth for each task.

What are the security and governance rules in production?

Secrets management least privilege approval gates and explicit rollback rules prevent unsafe production changes.

Target User

Use Cases