batch

Orchestrate multi-agent tasks in sequential batches and write results to work/batch1-results.md.

Updated Apr 29, 2026
One-click install
npx skills add https://github.com/MantisWare/BizForge --skill batch-mantisware
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: batch
Source: https://github.com/MantisWare/BizForge/tree/main/library/skills/workflow/batch
Command: npx skills add https://github.com/MantisWare/BizForge --skill batch-mantisware

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Batch processing helps teams run multiple AI agents efficiently by reducing token consumption and maintaining cost-effective orchestration.

Core Features & Use Cases

  • Analyze task complexity and identify required agents
  • Plan batches of 3-5 agents with a dedicated context window per batch
  • Execute batches sequentially with agents within a batch running in parallel
  • Synthesize batch results into a final output
  • Use Case: orchestrating a full-stack feature with multiple agents across frontend, backend, and tests

Quick Start

Run a task with /batch to start batching and let the orchestrator execute the first batch.

Frequently Asked Questions about batch

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

FAQPage Schema
How do I reduce token consumption when orchestrating multiple AI agents?

You can reduce token consumption in multi-agent orchestration by grouping tasks into batches of 3-5 agents. This approach uses dedicated context windows per batch and executes sequentially to maintain cost-effective workflow efficiency.

What is multi-agent batching and when should I use it?

Multi-agent batching is an orchestration technique that groups AI tasks into 3-5 agent batches executed sequentially with parallel execution within each batch. You should use it when coordinating complex workflows like full-stack feature development across frontend, backend, and tests.

How do I orchestrate a full-stack feature with parallel agents across frontend and backend?

You can orchestrate full-stack features by analyzing task complexity, planning batches of 3-5 agents with dedicated context windows, and executing them sequentially. The orchestrator synthesizes batch results and writes final outputs to work/batch1-results.md.

Can I run agents in parallel within a batch while keeping batches sequential?

Yes, agents within a batch run in parallel while batches themselves execute sequentially. This batching approach maintains isolated context windows per batch and synthesizes results into a final output after all planned batches complete execution.

How many agents should I group together for efficient multi-agent task batching?

You should group tasks into batches of 3-5 agents for efficient multi-agent batching. This batch size allows parallel execution within each batch while maintaining dedicated context windows and sequential batch processing to optimize token efficiency.

Do I need any dependencies to run batched multi-agent orchestration?

No external dependencies are required to run batched multi-agent orchestration. You can start the batching process by running a task with the /batch command, which lets the orchestrator analyze task complexity and execute the first batch automatically.