CI/CD Pipeline Architecture AGENTS.md Template

Overview

The AGENTS.md template is a project-level operating manual for AI coding agents implementing a CI/CD pipeline architecture. It governs single-agent workflows and multi-agent orchestration, clarifying roles, memory, sources of truth, handoffs, tool access, and governance to keep CI/CD iterations auditable and repeatable.

When to Use This AGENTS.md Template

Standardize agent behavior for CI/CD pipelines used by AI coding agents.
Enable predictable multi-agent handoffs across build, test, and deployment steps.
Provide a reference model for tool governance, secret handling, and escalation to human review.
Reduce context drift and architecture drift through explicit constraints and memory rules.

Copyable AGENTS.md Template

# AGENTS.md

Project role: CI/CD Automation Lead; Agent roster: Planner, Implementer, Reviewer, Tester, Researcher, Domain Specialist; Supervisor/Orchestrator: Orchestrator agent coordinating plans, actions, and handoffs across all agents.

Agent responsibilities:
- Planner: designs the CI/CD plan and sequencing of steps; maintains the master plan and acceptance criteria.
- Implementer: translates the plan into executable steps, config changes, and artifact generation.
- Reviewer: validates changes against policy, quality gates, and security constraints.
- Tester: runs unit/integration tests and verifies end-to-end behavior in a staging-like environment.
- Researcher: gathers external data, docs, and APIs as needed; ensures data usage complies with policy.
- Domain Specialist: provides domain-specific constraints, risk assessment, and correctness checks.

Supervisor/Orchestrator behavior:
- Maintains a single source of truth and ensures all agents update a central memory store.
- Oversees handoffs, detects drift, and reassigns tasks if blockers appear.
- Enforces tool access controls, secret protection, and audit logging.

Handoff rules:
- Planner → Implementer: deliver a clear, scoped plan with acceptance criteria.
- Implementer → Reviewer: present changes, config diffs, and test results.
- Reviewer → Tester: approve tests and gating criteria.
- Tester → Researcher/Domain Specialist: fetch data or verify domain constraints when needed.
- Researcher/Domain Specialist → Planner: summarize findings and update the plan.

Context, memory, and source of truth:
- Use a central repository-anchored memory, updated after every handoff.
- All decisions and assumptions must be captured in the AGENTS.md template and linked artifacts.
- Source of truth includes code, configuration, test results, and audit logs.

Tool access and permission rules:
- Access only approved tools with scoped permissions.
- Secrets must be stored in a vault and never hard-coded.
- API keys must be rotated per policy and never exposed in logs.

Architecture rules:
- Modularity, idempotence, and traceability are mandatory.
- Each step should be auditable and reversible where possible.
- Use environment-specific configurations and feature flags for production safety.

File structure rules:
- Place CI/CD configuration next to project specs; avoid duplicating configs across branches.
- Keep agent-specific configs under an agent-handbooks directory.

Data, API, or integration rules:
- Validate inputs and sanitize outputs; never trust external data without validation.
- Follow rate limits and error-handling policies for external services.

Validation rules:
- All changes must pass unit and integration tests before promotion.
- Gate deployments with a manual or automated approval check when required.

Security rules:
- Never expose secrets in logs or code.
- Enforce least privilege for all agents and services.

Testing rules:
- Run unit, integration, and end-to-end tests in a staging environment.
- Verify rollback procedures work before production deployment.

Deployment rules:
- Deploy to staging first, then promote to production after approval.
- Record all deployment steps and outcomes in audit logs.

Human review and escalation rules:
- Escalate blockers to a human in case of policy violations or failed tests.
- Maintain an escalation trail with time stamps and responsible party.

Failure handling and rollback rules:
- If a deployment fails, roll back to the last known-good state automatically when possible.
- Preserve artifact integrity and provenance for post-mortem analysis.

Things Agents must not do:
- Do not modify production state directly without approval.
- Do not bypass tests or skip required gates.
- Do not drift from architecture or memory constraints.
- Do not perform unsupervised production changes.

Recommended Agent Operating Model

The operating model defines role boundaries, decision rights, and escalation paths for CI/CD automation using AI coding agents. Planner, Implementer, Reviewer, Tester, Researcher, and Domain Specialist each have clear decision boundaries, with the Orchestrator enforcing handoffs and integrity across the pipeline.

Recommended Project Structure

ci-cd-pipeline/
  config/
  infra/
  build/
  test/
  deploy/
  agents/
    planner/
    implementer/
    reviewer/
    tester/
    researcher/
    domain-specialist/
  orchestrator/
  artifacts/
  docs/

Core Operating Principles

Idempotence in every step to prevent repeated effects on retries.
Single source of truth with explicit memory and provenance.
Strict handoffs with checks and gates between agents.
Least privilege for tool access and secrets management.
Auditable actions with complete traceability.

Agent Handoff and Collaboration Rules

Planner provides a plan with acceptance criteria and success criteria before Implementer starts.
Implementer reports diffs, config changes, and test results to Reviewer.
Reviewer confirms policy, security, and quality gates before Tester proceeds.
Researcher supplies data, docs, and API references when requested by Domain Specialist.
Domain Specialist clarifies constraints; escalate to Planner if constraints are unmet.

Tool Governance and Permission Rules

Only approved tools may be used; permissions are scoped per task.
Secrets must live in a vault; never hard-coded or logged.
All API calls require auditing and must be reversible if possible.
Production changes require explicit approval gates.

Code Construction Rules

Write modular, testable CI/CD steps with clear input/output contracts.
Validate schemas, configurations, and deployments before execution.
Avoid duplicating logic across steps; prefer reusable templates.
Ensure deterministic builds and reproducible artifacts.

Security and Production Rules

Operate in a least-privilege model; rotate credentials and use vaults.
Protect secrets; do not embed in code or logs.
Audit all access and changes to production systems.

Testing Checklist

Unit tests for individual steps and deterministic outputs.
Integration tests across the CI/CD toolchain and mocked services.
End-to-end tests in a staging environment with rollback checks.

Common Mistakes to Avoid

Skipping gates; deploying without proper tests and approvals.
Hiding context drift or memory updates outside the AGENTS.md templates.
Allowing unmanaged secrets or hard-coded credentials.
Failing to document handoffs and decisions for future audits.

FAQ

What is AGENTS.md Template for CI/CD?

It provides a concrete operating manual for AI coding agents to govern a CI/CD pipeline and multi-agent orchestration.

Who uses this template?

Developers, platform teams, and engineering leaders implementing AI-driven CI/CD workflows.

How are handoffs enforced?

The Orchestrator enforces handoffs through explicit criteria, gates, and documented state between Planner, Implementer, Reviewer, and Tester.

How are secrets and production credentials managed?

Secrets live in a vault, are rotated per policy, and are never logged or embedded in code.

What happens if a deployment fails?

Automatic rollback to the last known-good state when possible, with an auditable post-mortem.

Target User

Use Cases