parallel-session-orchestration

What problem does it solve?

This Skill dramatically increases your AI agent's efficiency by enabling it to execute multiple tasks concurrently in isolated cloud sandboxes. It overcomes the limitations of sequential processing, effectively doubling throughput for multi-project or independent workstreams.

Core Features & Use Cases

• Concurrent Task Execution: Runs multiple agent tasks simultaneously in parallel sandboxes, reducing overall completion time.
• Real-time Progress Monitoring: Provides live updates on the status of each parallel task, keeping you informed without waiting.
• Isolated Sandboxes: Each task runs in its own environment, preventing conflicts and ensuring reliable execution across different repositories or projects.
• Use Case: You have three independent tasks: "fix auth bug in repo-A," "update dependencies in repo-B," and "add unit tests to repo-C." This skill orchestrates all three to run in parallel, completing them in the time it takes for the longest single task, rather than the sum of all three.

Quick Start

Example: Orchestrate multiple tasks to run in parallel

import asyncio

async def orchestrate_parallel(tasks): sessions = [] for task in tasks: session = await create_sandbox_session(task) # Assume create_sandbox_session is defined sessions.append(session) results = await asyncio.gather(*[session.execute() for session in sessions]) return merge_results(results) # Assume merge_results is defined

tasks = [ {'name': 'fix-auth-bug', 'repo': 'https://github.com/org/repo-a', 'instructions': 'Fix auth timeout'}, {'name': 'update-deps', 'repo': 'https://github.com/org/repo-b', 'instructions': 'Update dependencies'} ] results = asyncio.run(orchestrate_parallel(tasks))

Results from both tasks are available simultaneously