parallel-agents

Name: parallel-agents
Availability: InStock
Author: parcadei

Launch up to 15 concurrent agents with file-based status tracking.

3.9k|296|Updated Dec 23, 2025

Search Tags:#context management #agents #orchestration #efficiency #batch processing #parallelism

Ready to run

npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill parallel-agents-parcadei

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: parallel-agents
Source: https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/parallel-agents
Command: npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill parallel-agents-parcadei

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses context bloat and token inefficiency when running multiple agents simultaneously by providing a structured pattern for parallel execution and status tracking.

Core Features & Use Cases

Parallel Execution: Launch up to 15 agents concurrently for tasks that can be parallelized.
Context Management: Avoids TaskOutput calls to prevent context bloat, using file-based confirmations instead.
Status Monitoring: Provides clear methods to track the completion status of parallel agent batches.
Use Case: When performing a large-scale data backfill across multiple providers, use this Skill to launch agents for each provider in parallel, monitoring their progress via a shared status file.

Quick Start

Use the parallel-agents skill to launch a batch of agents for provider backfill, ensuring each agent runs in the background and reports completion to a status file.

Frequently Asked Questions about parallel-agents

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

FAQPage Schema

How do I prevent context bloat when running multiple agents in parallel?▼

To prevent context bloat during parallel agent execution, use file-based status reporting instead of TaskOutput calls to track completion. This approach optimizes token usage and provides structured monitoring for concurrent agent tasks.

How many agents can I launch concurrently for batch processing?▼

You can launch up to 15 agents concurrently for batch processing tasks. This parallel execution capability allows efficient handling of large-scale operations like distributed research or data backfill across multiple providers.

What is the best way to track the completion status of parallel agent batches?▼

The best way to track parallel agent batch completion status is through a shared status file. Agents running in the background report their completion to this file, enabling efficient monitoring without context bloat.

Can I run agents in the background for distributed research tasks?▼

Yes, you can run agents in the background for distributed research tasks. This Skill supports background execution with batch size limitations up to 15 concurrent agents, reporting completion via file-based confirmations.

Why does running concurrent agents cause token inefficiency?▼

Concurrent agents cause token inefficiency when TaskOutput calls accumulate large amounts of context data. Using file-based confirmations instead of direct output calls prevents this context bloat and optimizes overall token usage.