AGENTS.md Template: Write-Behind Cache Architecture

Overview

This AGENTS.md template defines the operating context for a write-behind cache workflow used by AI coding agents. It governs single-agent work and multi-agent orchestration where workers write to a cache asynchronously, propagate writes to the data store, and maintain consistency with the source of truth. It provides a copyable operating manual that teams can paste into AGENTS.md to start and govern an end-to-end cache write-back pattern.

When to Use This AGENTS.md Template

• When implementing an AI-driven write-behind or write-back cache that batches and propagates writes to a backing store.
• When coordinating multiple agents for cache write, validation, and rollback in a production-like environment.
• When you need explicit handoff rules, memory scope, and source-of-truth constraints to avoid context drift.
• When enforcing tool governance, security, and deployment rules across agents and environments.

Copyable AGENTS.md Template

# AGENTS.md
Project: Write-Behind Cache Architecture for AI Coding Agents

Project Role
- Platform engineer or AI platform owner responsible for cache strategy and agent coordination.

Agent Roster and Responsibilities
- Planner: designs work plan, sequences tasks, and allocates flows between cache writer and validator.
- CacheWriter: performs write-back to backing store (e.g., database, durable storage) and updates in-memory cache.
- DataValidator: validates data integrity, formats, and constraints before persisting.
- HandoffAgent: manages handoffs between stages and ensures context propagation.
- Monitor: records metrics and detects anomalies.
- Auditor: ensures policy compliance and security controls.

Supervisor or Orchestrator Behavior
- Central orchestrator coordinates tasks, enforces timeouts, and retries failed steps.
- Maintains a single source of truth for task state and artifacts.

Handoff Rules Between Agents
- Planner -> CacheWriter: pass task, input context, and expected output schema.
- CacheWriter -> DataValidator: pass persisted data and validation report.
- DataValidator -> Monitor: pass validation result and health signals.

Context, Memory, and Source-of-Truth Rules
- Context is passed through task headers and stored in a compact in-memory store.
- Source-of-truth: primary backing store; memory cache contains recent writes.
- Memory lifecycle: cache entries expire after a defined TTL and are evicted in LRU order.

Tool Access and Permission Rules
- Cache store access: read/write to Redis or equivalent with scoped credentials.
- Secrets: stored in a secrets vault; agents receive short-lived tokens.
- API access: only to authorized internal services with audit logs.

Architecture Rules
- Separation of concerns: planner orchestrates; writer persists; validator validates.
- Event-driven: each step emits an event for observability and traceability.
- Idempotent operations: operations are safe to retry.

File Structure Rules
- One repository with domain folders for planner, writer, validator, monitor, and auditor.
- Central orchestrator config and policy files at the top level.
- Tests under /tests with integration tests for end-to-end flows.

Data, API, or Integration Rules
- Validate input schemas before writes; reject invalid data.
- Use versioned APIs; include resource identifiers.

Validation Rules
- Acceptance criteria: successful write-back to the backing store and cache consistency.
- Edge-case tests for failures and retries.

Security Rules
- Principle of least privilege for all agents.
- Secrets never logged; rotate keys regularly.

Testing Rules
- Unit tests for each agent and the orchestrator.
- End-to-end tests simulating write-back scenarios.
- Chaos testing for failure modes.

Deployment Rules
- Canary deployments for cache write path.
- Feature flags to enable/disable the write-behind flow.

Human Review and Escalation Rules
- Human review on failed completions, policy violations, or security alerts.
- Escalation path with clear owners and SLAs.

Failure Handling and Rollback Rules
- On failure, rollback to the previous known-good cache entry and retry policy.
- Ensure idempotent writes to prevent duplicate updates.

Things Agents Must Not Do
- Do not bypass the source-of-truth store.
- Do not perform unverified migrations on live data.
- Do not share credentials in logs.

Recommended Agent Operating Model

Roles and decision boundaries for clean handoffs and escalation paths between Planner, CacheWriter, DataValidator, and Monitor. Escalations route to the Auditor when policy or security anomalies are detected.

Recommended Project Structure

write-behind-cache/
├── planner/
│   └── planner.ts
├── writer/
│   └── cache_writer.ts
├── validator/
│   └── data_validator.ts
├── monitor/
│   └── monitor.ts
├── auditor/
│   └── policy_auditor.ts
├── orchestrator/
│   └── cache_orchestrator.ts
├── memory/
│   └── cache_memory.json
├── services/
│   └── cache_api_client.ts
├── tests/
│   └── end_to_end.test.ts
└── configs/
    └── policy.yml

Core Operating Principles

• Single source of truth for task state.
• Idempotent operations and retry-safe flows.
• Clear ownership and explicit handoffs between agents.
• Observability across all steps with auditable logs.

Agent Handoff and Collaboration Rules

• Planner defines the sequence and passes task context to CacheWriter.
• CacheWriter persists to backing store and returns status to Planner.
• DataValidator validates persisted data and signals to Monitor.
• Monitor surfaces alerts; Auditor can intervene for policy issues.

Tool Governance and Permission Rules

• Only approved tools and APIs; secrets stored securely and rotated.
• All writes must be logged with a traceable correlation ID.
• Production systems require approval gates for changes.

Code Construction Rules

• Use modular, testable components with clear interfaces.
• Respect rate limits and backoffs for external calls.
• Documentation must reflect changes and policy updates.

Security and Production Rules

• Encrypt data in transit and at rest where applicable.
• Enforce role-based access control for all agents.
• Audit all privilege escalations and access to secrets.

Testing Checklist

• Unit tests for each agent module.
• Integration tests for end-to-end write-behind flow.
• Failover and rollback tests.
• Security and access control tests.

Common Mistakes to Avoid

• Skipping source-of-truth validation during writes.
• Ignoring idempotency in retry paths.
• Overlooking data consistency between cache and backing store.

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FAQ

What is this AGENTS.md template used for?

It provides a copyable operating manual for a write-behind cache workflow with multi-agent orchestration.

Can this template cover both single-agent and multi-agent patterns?

Yes, it defines roles, handoffs, and governance for both modes and clarifies when to escalate.

Where should I paste the template?

Into the project-level AGENTS.md at the repository root or a docs directory intended for agent governance.

How are agent handoffs enforced?

Handoffs are explicit in planner to writer to validator steps, with memory and context propagation constraints.

What security considerations are included?

Least privilege, secrets vaults, auditing, and encrypted data flows are defined by default.