Timeout Policy Design AGENTS.md Template

Overview

Direct answer: This AGENTS.md template defines a timeout policy design workflow for AI coding agents and multi-agent orchestration, enabling bounded, observable, and auditable agent behavior.

This page documents a concrete AGENTS.md template for timeout policy design, describing how planners, implementers, reviewers, testers, researchers, and domain specialists collaborate to set, enforce, and recover from timeouts in AI coding agent workflows. It covers both single-agent and multi-agent orchestration patterns, including handoffs, memory, source-of-truth, and governance constraints.

When to Use This AGENTS.md Template

• When designing timeout policies for AI coding agents involved in API calls, long-running computations, or external tool invocations.
• When coordinating a multi-agent design where planners set budgets and implementers enforce them with safe fallbacks.
• When you need explicit handoff rules, escalation paths, and human review for timeout-related risks.
• When enforcing source-of-truth and memory constraints to avoid context drift during timeout workflows.

Copyable AGENTS.md Template

# AGENTS.md

Project Role: Timeout Policy Design for AI coding agents

Agent Roster and Responsibilities:
- Planner: defines timeout goals, SLOs, budget, and escalation thresholds.
- Implementer: encodes timeout logic, cancellation, and time-constrained execution paths.
- Reviewer: validates timeout correctness, safety limits, and fallback behavior.
- Tester: creates tests for timeout scenarios and recovery paths.
- Researcher: gathers requirements from APIs, services, and external tools.
- Domain Specialist: ensures domain-specific timeout constraints and integration constraints.

Supervisor / Orchestrator Behavior:
- Central orchestrator tracks budgets, timeouts, and progress across agents.
- Enforces memory boundaries, versioned artifacts, and single source of truth.
- Initiates handoffs on boundary events (timeout nearing, timeout exceeded, or error).

Handoff Rules Between Agents:
- Planner -> Implementer: deliver timeout specs and interface contracts.
- Implementer -> Reviewer: deliver code, tests, and timeout configurations.
- Reviewer -> Implementer: approve changes or request redesign.
- Implementer -> Tester: provide test cases and CI hooks.
- Tester -> Planner: report results and recommended adjustments.

Context, Memory, and Source-of-Truth Rules:
- All timeout configuration lives in a version-controlled policy doc and a centralized memory store.
- Use a single source of truth for timeouts (policy.yaml) and a separate ledger for execution traces.

Tool Access and Permission Rules:
- Implementations may access timeouts configuration, API client libraries, and logging facilities.
- Secrets must be accessed via approved vaults; no hard-coded credentials.

Architecture Rules:
- Central timeout orchestrator with pluggable policy adapters.
- Each agent operates in isolated contexts with clear interfaces.

File Structure Rules:
- timeout-policy/
  - orchestrator/
  - planner/
  - implementer/
  - reviewer/
  - tester/
  - researcher/
  - domain/
  - config/
  - docs/
  - tests/

Data, API, or Integration Rules:
- All external calls must be wrapped with timeout controls and cancellation tokens.
- Implement default timeouts and per-call overrides with safe fallbacks.

Validation Rules:
- Timeouts must be measurable and auditable; all events must be logged with timestamps.
- Tests cover: timeout near, timeout exceeded, cancellation behavior, and fallback correctness.

Security Rules:
- Do not expose credentials; use secret vaults; limit access to production timeouts.
- Audit logs must be immutable and tamper-evident.

Testing Rules:
- Unit tests for timeout helpers; integration tests for API calls with simulated latency.
- End-to-end tests verify orchestrator handles timeout events correctly.

Deployment Rules:
- Deploy orchestrator and policy changes together; roll back if timeouts regress.

Human Review and Escalation Rules:
- If a timeout introduces a risk of data loss or policy violation, escalate to the on-call engineer.
- All changes require a two-person review for production timeouts affecting user flows.

Failure Handling and Rollback Rules:
- On timeout, switch to safe fallback or cached result; if failure persists, revert to previous policy version.

Things Agents Must Not Do:
- Do not bypass timeout checks or execute without budget checks.
- Do not modify production timeouts without approval.
- Do not use unsafe default timeouts that risk crash loops.

Recommended Agent Operating Model

Roles and decision boundaries for timeout policy design: Planner defines budgets and outcomes; Implementer translates them into code; Reviewer confirms safety; Tester validates; Researcher and Domain Specialist supply constraints. Escalation paths ensure human review when risk is detected.

Recommended Project Structure

timeout-policy-design/
  orchestrator/
  planner/
  implementer/
  reviewer/
  tester/
  researcher/
  domain/
  config/
  docs/
  tests/

Core Operating Principles

• Single source of truth for timeout policies and budgets.
• Deterministic, auditable handoffs with versioned artifacts.
• Bounded execution with explicit failure and recovery paths.
• Separation of concerns across planner, implementer, reviewer, tester, researcher, and domain specialist agents.

Agent Handoff and Collaboration Rules

Concrete rules to coordinate handoffs: planner designs budgets; implementer enforces; reviewer validates; tester tests; researcher and domain specialist provide domain constraints; orchestrator coordinates across all roles.

Tool Governance and Permission Rules

• Thou shalt not access secrets outside approved vaults.
• All changes require approvals; production timeouts require on-call sign-off.
• Use read-only access for planning after approval; write access only via controlled pipelines.

Code Construction Rules

• Use cancelable asynchronous tasks with safe timeouts and cancels.
• Time-based tests must simulate latency accurately and deterministically.
• All timeout settings should be parameterized and versioned.

Security and Production Rules

• Secrets stored in vaults; never hard-coded.
• Production timeouts must be instrumented and monitored; alert on deviations.

Testing Checklist

• Unit tests for timeout helpers and adapters.
• Integration tests with simulated latency and failures.
• End-to-end tests for orchestrator handling of timeout events.

Common Mistakes to Avoid

• Assuming timeouts are rare and not modeling edge cases.
• Ignoring human review for risky timeout changes.
• Overriding timeouts without proper budget controls.

Related implementation resources: AI Use Case for Content Marketers Using Wordpress To Auto-Translate Blog Posts Into Multiple Languages and AI Agent Use Case for Manufacturing Buyers Using Supplier Lead Time Trends To Automatically Adjust Raw Material Reorder Dates.

FAQ

What is this AGENTS.md Template for timeout policy design?

This template codifies a repeatable, auditable workflow for designing, validating, and enforcing timeout policies across AI coding agents and their orchestration.

Who should use this template and what is the intended outcome?

Engineering teams implementing timeouts in AI coding agents; outcome is a safe, predictable, documented policy with auditable traces.

How are timeouts governed across agents?

Policies define per-call timeouts, global budgets, escalation thresholds, and fallback strategies; planners set budgets, others implement, test, and review.

How do agents escalate or hand off when a timeout occurs?

Orchestrator triggers handoffs to escalate to human review when thresholds are breached; failures roll back to a safe state or cached result.

What security and governance rules apply to timeout workflows?

Access to secrets is restricted; production changes require approvals; all actions are logged and auditable.