AGENTS.md Template: Write-Through Cache Architecture

Overview

The AGENTS.md template documents a write-through cache architecture workflow for AI coding agents and shows how to govern single-agent and multi-agent orchestration. It codifies the operating context, roles, and handoffs so teams can implement a reliable, auditable write-through path where cache writes are propagated to the canonical data store with clear governance and escalation paths.

Direct answer: This template defines roles, handoffs, and governance for a write-through cache workflow, enabling consistent data and cache coherence across agents and systems.

When to Use This AGENTS.md Template

When implementing a write-through cache layer to ensure every cache write is reflected in the canonical datastore.
When coordinating multi-agent activities to maintain cache coherence and data integrity.
When you need explicit handoff rules, memory/state management, and source-of-truth governance.
When you want a copyable, project-level operating context that can be pasted into an AGENTS.md file for a given workflow.

Copyable AGENTS.md Template

# AGENTS.md

Project Role: Write-Through Cache Orchestration for AI Coding Agents

Agent roster and responsibilities:
- PlannerAgent (Orchestrator): coordinates the end-to-end write-through path, validates input, assigns tasks, enforces preconditions, and triggers cache_writer and db_writer.
- CacheWriterAgent: writes to the cache (e.g., Redis) with proper TTL, ensures cache coherence, and returns a write_id.
- DBWriterAgent: writes to the canonical datastore (e.g., Postgres) with transaction semantics and returns a write_id.
- CacheConsistencyAgent: verifies that the cache value matches the DB value after writes.
- AuditorAgent: logs outcomes, flags anomalies, and triggers human review when needed.

Supervisor or orchestrator behavior:
- Planner coordinates all steps, enforces preconditions, and handles rollback if any step fails. It maintains a single source of truth for the operation and ensures idempotent execution.

Handoff rules between agents:
- Step 1: Planner validates payload and creates an action plan with a unique write_id; Step 2: CacheWriter writes to cache; Step 3: DBWriter writes to DB; Step 4: CacheConsistency validates; Step 5: On success, commit and notify all agents; Step 6: Auditor logs results.

Context, memory, and source-of-truth rules:
- Canonical source of truth is the canonical datastore (DB). The cache is a mutable shadow. Memory stores only ephemeral task context and lineage for the current write operation.
- All agents should read from the canonical DB for truth; cache should be updated to reflect DB state in a deterministic manner.

Tool access and permission rules:
- Tools: Redis cache, DB API, and optional message bus for coordination. Access is restricted by role; never share credentials in memory.

Architecture rules:
- Clear separation: API Gateway & Ingress & Orchestrator (Planner) & Agents (CacheWriter, DBWriter, CacheConsistency, Auditor).
- Use idempotent operations and a deterministic write_id to tie cache and DB actions.

File structure rules:
- Separate agent modules and shared utilities; avoid coupling unrelated services into the AGENTS.md template block.

Data, API, or integration rules when relevant:
- Serialize payloads deterministically; ensure schema compatibility across cache and DB.

Validation rules:
- Validate required fields; ensure idempotent behavior; verify that the write_id is present and unique per operation.

Security rules:
- Secure all secrets; encrypt in transit; restrict access to cache and DB APIs; audit trails for sensitive writes.

Testing rules:
- Unit tests for each agent, integration tests for end-to-end write-through flow, and contract tests for API boundaries.

Deployment rules:
- Prefer canary deployment for planner changes; require feature flags for risky changes; monitor rollback triggers.

Human review and escalation rules:
- Escalate to a human review if multiple consecutive failures occur or if data integrity is suspected.

Failure handling and rollback rules:
- If cache write succeeds but DB write fails, perform a rollback to remove the cache entry or mark as stale; if DB write succeeds but cache write fails, rollback DB write or flag for retry; maintain idempotence and traceability.

Things Agents must not do:
- Do not bypass the planner; do not perform writes to DB or cache without planning; do not mutate canonical data without approval; do not deploy without tests or approvals.

Recommended Agent Operating Model

Roles and decision boundaries: - PlannerAgent: determines whether a given write should proceed, handles orchestration logic, and enforces end-to-end invariants. - CacheWriterAgent: low-latency write path for cache; must surface write_id back to planner; cannot bypass DB to indicate success. - DBWriterAgent: guarantees atomic write to the canonical datastore; must coordinate with planner for rollback on failure. - CacheConsistencyAgent: cross-checks cache and DB values after write; suggests remediation if mismatch detected. - AuditorAgent: records outcomes, triggers escalation when anomalies occur, and maintains an immutable log for audit. Escalation paths: - If the planner detects repeated failures or data drift exceeds threshold, escalate to engineering lead and product owner; enable human review and potential rollback.

Recommended Project Structure

projects/write-through-cache-agents/
├── src
│   ├── agents
│   │   ├── planner
│   │   │   └── planner.go
│   │   ├── cache_writer
│   │   │   └── cache_writer.go
│   │   ├── db_writer
│   │   │   └── db_writer.go
│   │   ├── cache_consistency
│   │   │   └── consistency.go
│   │   └── auditor
│   │       └── auditor.go
│   ├── config
│   │   └── config.yaml
│   └── tests
│       └── end_to_end_test.go
└── README.md

Core Operating Principles

Single source of truth: canonical datastore is the DB; cache is a deterministic shadow.
Idempotence: repeated writes with same write_id must not produce duplicate effects.
Deterministic handoffs: planners explicitly define task boundaries and success criteria for each agent.
Explicit memory: avoid hidden state; store transient context in Planner memory only.
Observe and audit: every operation is logged and auditable.

Agent Handoff and Collaboration Rules

Planner → CacheWriter: provide write_id, payload, and TTL policies; ensure preconditions pass.
CacheWriter → DBWriter: return write_id and status; planner coordinates rollback if DB fails.
DBWriter → CacheConsistency: trigger validation after both writes complete.
CacheConsistency → Auditor: report success or mismatch; planner commits or retries.
In case of failure, planner initiates rollback and notifies all participants; avoid partial commits.

Tool Governance and Permission Rules

Cache access: Redis commands restricted to CacheWriterAgent with TTL policies.
DB access: DBWriterAgent uses transactional writes with proper isolation levels; read-your-writes semantics respected.
Secrets and credentials managed via a secure vault; no hard-coded tokens.
All tool calls are auditable and traceable to a write_id.
No direct web API writes bypass the orchestrator.

Code Construction Rules

Use deterministic serialization for payloads; include write_id as a first-class field.
Ensure idempotent writes across cache and DB; never assume cache state is persistent after restart.
Validate input schema strictly before planning actions.
Decouple read path from write path to avoid contention.

Security and Production Rules

Encrypt data in transit; use TLS everywhere; enforce least privilege on all agents.
Store secrets in a centralized vault; rotate credentials periodically.
Monitor for anomaly signals; implement rate limits for write requests.
Ensure rollback procedures are tested and can be executed in production with low risk.

Testing Checklist

Unit tests for Planner, CacheWriter, DBWriter, and CacheConsistency modules.
Integration tests for end-to-end write-through path with positive and negative cases.
Contract tests for payload validation and serialization across components.
Canary tests for production-like traffic before full rollout.

Common Mistakes to Avoid

Bypassing the orchestrator or performing uncoordinated writes to DB or cache.
Ignoring idempotence and allowing duplicate write_ids.
Unreadable failure modes or missing rollback paths.
Relying on cache as the source of truth without ensuring DB consistency.

FAQ

What is the purpose of this AGENTS.md Template for write-through cache architecture?

It defines roles, handoffs, and governance for a write-through cache workflow to ensure data consistency and clear collaboration among AI coding agents.

How does multi-agent orchestration maintain cache coherence?

Through explicit write-through steps, deterministic write_ids, and a validation agent that confirms cache equals the canonical DB after writes; rollback is triggered on any mismatch.

What are the handoff rules between Planner, CacheWriter, and DBWriter?

Planner validates input and generates a plan; CacheWriter updates the cache; DBWriter updates the database; CacheConsistency validates results; Auditor logs outcomes and planner commits or retries.

How is security managed in this AGENTS.md Template?

Secrets are stored in a vault, communications are TLS-encrypted, access is role-based, and all actions are auditable with write_id tracing.

Target User

Use Cases