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parallel-orchestration

Decompose tasks into dependency graphs and coordinate parallel AI agent execution with immutable snapshots.

1|Updated Sep 11, 2026
Search Tags:#workflow#parallel execution#multi-agent#orchestration#github issues#dependency graph#stacked pr
One-click install
npx skills add https://github.com/rebuildup/my-web-2026 --skill parallel-orchestration-rebuildup
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: parallel-orchestration
Source: https://github.com/rebuildup/my-web-2026/tree/main/skills/parallel-orchestration
Command: npx skills add https://github.com/rebuildup/my-web-2026 --skill parallel-orchestration-rebuildup

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Coordinating multiple AI agents on a shared codebase risks conflicting writes, stale results, and lost work when agents fail. This Skill defines a Supervisor-based orchestration model that decomposes work into a dependency graph and integrates results safely. ## Core Features & Use Cases - Dependency-aware decomposition: Breaks GitHub Issues into a task graph, spawning only Ready or stack-ready nodes within WIP and resource limits. - Immutable contracts: Enforces spawn contracts (base snapshot, execution_generation, policies) and result contracts (commit/ref, validation results) so stale generations are never merged. - Stacked PR delivery: Supports stacked pull requests with predecessor snapshot pinning, Draft PR lifecycle rules, and revalidation when predecessors change. - Use Case: Split a cross-boundary feature into three GitHub Issues, spawn isolated workers per node, and have the Supervisor integrate validated results in dependency order while a cold reviewer checks each candidate snapshot. ## Quick Start Ask the agent to decompose this GitHub Issue into a dependency graph and orchestrate parallel workers with immutable snapshots and stacked PRs.

Frequently Asked Questions about parallel-orchestration

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

FAQPage Schema
How do I run multiple AI coding agents in parallel safely?▼

Assign each worker one isolated mutable runtime and forbid shared writes to the working tree or Git index. Pass immutable snapshots from parent to child and return immutable commits plus validation results, with a Supervisor owning integration.

How to manage stacked pull requests with dependent tasks?▼

A node can start stack-ready when its predecessor has a reviewable immutable snapshot, recording the predecessor Issue/PR and exact commit SHA. If the predecessor changes, treat downstream branches as stale, reconcile the base, and rerun required validation.

What is execution_generation in multi-agent orchestration?▼

execution_generation is a mandatory counter on every mutable worker task and result, starting at 1 and advanced atomically by the Supervisor on recovery or reassignment. Results whose generation does not match the current value are never auto-integrated.

When should I not parallelize AI agent tasks?▼

Mechanical or localized execution profiles default to solo execution with focused validation. If true isolation is unavailable, fall back to parallel read-only research or safe serial implementation instead of a shared mutable workspace.

What happens to child agents when the parent agent fails?▼

Safe children are not automatically discarded when a parent stops. A recovered Coordinator rediscovers children via the Supervisor, reconciles their state, and integrates completed results only after verifying snapshots, predecessors, and generation.

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