AGENTS.md Template for Business Continuity Planning

Overview

Direct answer: This AGENTS.md template for Business Continuity Planning provides a complete operating manual for AI coding agents to govern both single-agent workflows and multi-agent orchestration during disruptions.

What it enables: clearly defined roles, memory and source-of-truth rules, tool governance, and escalation paths to ensure continuity, auditable decision making, and safe production changes.

When to Use This AGENTS.md Template

• You need a reproducible, audit-ready operating context for a BCP workflow involving AI coding agents.
• Your incident response requires coordinated actions across multiple agents (planner, implementer, researcher, domain specialist, reviewer, tester, orchestrator).
• You must enforce governance, memory management, and escalation rules during disruptions.

Copyable AGENTS.md Template

# AGENTS.md

Project Role: Business Continuity Planning (BCP) with AI coding agents in a multi-agent orchestration pattern.

Agent roster and responsibilities:
- Planner: perform business impact analysis, define recovery objectives, create a plan backlog.
- Implementer: execute continuity tasks, apply runbooks, adjust configurations to restore services.
- Researcher: gather data from systems, logs, runbooks, external sources.
- Domain Specialist: ensure regulatory, privacy, and security constraints are satisfied.
- Reviewer: validate outputs, check alignment with objectives, and approve transitions.
- Tester: run simulations, verify outcomes in test environments.
- Orchestrator: supervise workflow, enforce governance, and manage handoffs.

Supervisor or orchestrator behavior:
- The Orchestrator coordinates actions, persists context to memory, and enforces sources of truth. It triggers handoffs and ensures idempotent execution.

Handoff rules between agents:
- Planner -> Implementer: final plan is handed off with explicit tasks, data requirements, and success criteria.
- Implementer -> Reviewer: completion triggers validation; Reviewer can request changes.
- Researcher  Planner: return new data or constraints that may alter the plan.
- Domain Specialist -> Orchestrator: updates to constraints propagate through the workflow.

Context, memory, and source-of-truth rules:
- Memory: planVersion, incidentScenario, systemStatuses, runbooks, dataSources, auditLog.
- Sources of truth: runbooks repository, monitoring dashboards, incident tickets, change management system. All changes must be recorded with timestamps.

Tool access and permission rules:
- Tools: API clients, monitoring and logging interfaces, backup/restore utilities. Secrets stored in a vault with rotation.
- Permissions: least privilege; Researchers read-only; Implementers can execute tasks; Approvers can modify critical configurations.

Architecture rules:
- Central orchestrator with per-agent plugins; event-driven; idempotent; clear audit logs; deterministic prompts; no black-box actions.

File structure rules:
- Use a minimal, well-organized structure focused on BCP workflows; no unnecessary folders.

Data, API, or integration rules when relevant:
- Data minimization, encryption in transit, and masking for logs; standardized data interchange formats.

Validation rules:
- Each action must include a validation step: confirm status, verify backups, check runbooks, and log outcomes.

Security rules:
- Secrets management, access control, encryption, and secure deployment practices; require approvals for privileged actions.

Testing rules:
- Unit tests for prompts; integration tests for cross-agent handoffs; end-to-end tests in a staging environment.

Deployment rules:
- Deploy orchestrator changes via feature flags; support rollbacks; maintain incident timelines.

Human review and escalation rules:
- Escalate to humans if automated recovery cannot complete within SLA or data integrity is at risk.

Failure handling and rollback rules:
- Revert to last known good state; preserve incident timeline; notify owners; document rationale.

Things Agents must not do:
- Do not perform destructive changes without explicit approval; do not bypass memory rules; do not reveal secrets.

Recommended Agent Operating Model

Roles and decision boundaries: Planner defines the plan; Implementer executes within the approved plan; Researcher supplies data; Domain Specialist imposes constraints; Reviewer validates; Orchestrator coordinates and handles handoffs; Tester validates outcomes. Escalation paths exist for failure or ambiguity.

Recommended Project Structure

/bcp-agents
  /planner
  /implementer
  /researcher
  /domain-specialist
  /reviewer
  /tester
  /orchestrator
  /tools
  /docs
  /configs

Core Operating Principles

• Operate with a single source of truth and a memory ledger accessible to all agents.
• Enforce explicit handoffs and defined decision boundaries.
• Ensure idempotent actions and complete audit trails.
• Apply least-privilege access for tool usage and data access.
• Seek human review when uncertainty or risk exceeds thresholds.

Agent Handoff and Collaboration Rules

Rules for planner, implementer, reviewer, tester, researcher, and domain specialist in BCP workflows:

• Planner to Implementer: hand off plan with tasks, data requirements, and success criteria.
• Researcher to Planner: return new data or constraints that may alter the plan.
• Domain Specialist to Orchestrator: enforce constraints and propagate governance changes.
• Tester to Reviewer: deliver test results for validation; Reviewer approves or requests changes.
• Orchestrator to All: maintain state, emit events, and enforce memory and sources of truth.

Tool Governance and Permission Rules

• Execute only allowed commands; do not improvise privileged actions without approval.
• Avoid hard-coded secrets; use secrets vaults; rotate keys.
• Record all tool interactions in the audit log; require approvals for production changes.

Code Construction Rules

• Prompts and prompts templates must be explicit; include input validation steps.
• Outputs must be idempotent; no side effects without verification.
• Use structured data formats for exchange between agents.

Security and Production Rules

• Secrets management, encryption in transit, access controls, and network restrictions.
• Production changes require a change management workflow and human approval.

Testing Checklist

• Unit tests for prompts and expectations.
• Integration tests for cross-agent handoffs.
• End-to-end tests in staging that simulate a disruption scenario.

Common Mistakes to Avoid

• Skipping memory or source-of-truth maintenance; drift occurs when data is duplicated across agents.
• Skipping human review for critical changes; relying solely on automation for recovery.
• Over-permitting agents or bypassing approval gates.

Related implementation resources: AI Use Case for Sales Pipeline Reviews and Deal Risk Scoring and AI Agent Use Case for Wholesalers Using Multi-Currency Ledger Trackers To Calculate Foreign Exchange Risk Exposure Across Global Accounts.

FAQ

What is this AGENTS.md Template used for in Business Continuity Planning?

It defines a repeatable, auditable operating manual for AI coding agents to plan, simulate, and execute continuity strategies using a multi-agent orchestration pattern.

How does multi-agent orchestration work in this template?

It assigns distinct roles (Planner, Implementer, Researcher, Domain Specialist, Reviewer, Tester, Orchestrator) and defines handoffs, memory rules, and validation steps to coordinate actions.

What happens if a step fails in the workflow?

Failure handling and rollback rules specify reverting to the last good state, logging events, and escalating to human reviewers when automated recovery isn’t possible.

What are the security considerations included?

Secrets management, least-privilege access, encryption in transit, and approval gates protect critical data and production systems.

How is memory and sources of truth maintained?

A memory ledger and controlled source-of-truth anchors (runbooks, incident tickets, monitoring dashboards) ensure consistent context across agents.