maestro-ralph

Orchestrate Session/Run workflows with policy checks and terminal decision making.

76|5|Updated Jul 7, 2026
One-click install
npx skills add https://github.com/catlog22/pi-maestro-flow --skill maestro-ralph
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: maestro-ralph
Source: https://github.com/catlog22/pi-maestro-flow/tree/main/.pi/skills/maestro-ralph
Command: npx skills add https://github.com/catlog22/pi-maestro-flow --skill maestro-ralph

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill manages the policy loop for a canonical Session/Run chain so an AI can locate, resume, evaluate, and seal work without breaking state or bypassing gates.

Core Features & Use Cases

  • Session-aware orchestration: Locate an existing compatible session, recover paused work, or create a new session when needed.
  • Run lifecycle governance: Drive the shared run loop with dispatch, check, decision, retry, drift handling, and terminal sealing.
  • Policy and safety control: Enforce confidence thresholds, risk gating, goal audits, amendment flow, and recovery rules for high-stakes workflows.
  • Use Case: A developer asks the agent to continue an interrupted engineering task, and the Skill resumes the correct session, verifies progress, and decides whether to proceed, retry, or pause.

Quick Start

Use the maestro-ralph skill to continue the active session for my intent, apply the required policy checks, and tell me whether the run should proceed, retry, pause, or seal.

Frequently Asked Questions about maestro-ralph

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I resume an interrupted AI agent workflow without breaking its state?

Session orchestration locates the existing compatible session, recovers paused work, and applies policy checks to safely resume an interrupted agent workflow without breaking state.

What is drift control in long-running agent chains and when do I need it?

Drift control evaluates whether an agent chain is偏离 its original goal during execution. You need it for long-running workflows and interrupted engineering tasks to ensure auditable goal-driven execution.

How to enforce confidence thresholds and risk gating for autonomous agent runs?

Apply policy gating to the run loop to enforce confidence thresholds, risk gating, and goal audits. This ensures safe terminal decision making by deciding whether to proceed, retry, pause, or seal.

Can I use session orchestration to manage retry budgets for high-stakes engineering tasks?

Yes, session orchestration supports interrupted engineering tasks and high-stakes workflows by applying retry budgets, recovery rules, and shared run-loop compliance to manage state safely.

What is the best way to seal a completed agent run and audit its final decisions?

Drive the shared run loop through dispatch, check, and decision phases to reach terminal sealing. This provides an auditable record of the final goal-driven execution and policy compliance.

Why does my agent workflow bypass safety gates during automated session recovery?

Without policy gating, session recovery can bypass safety checks. You need confidence gating, drift evaluation, and recovery rules to enforce shared run-loop compliance and manage state safely.