What are the four agent types defined in this skill?

The skill categorizes agents into Explore (research/analysis), Plan (architecture/design), Bash (commands/ops), and Edit (implementation/refactoring).

Can this skill help with failure recovery?

Yes, it includes standard patterns for automated retries, task reassignment, subtask decomposition, and checkpoints to ensure workstreams can recover from errors.

How does it handle task dependencies?

It generates a dependency graph to identify which tasks are blockers and which are independent, allowing for maximum parallelization without breaking the build.

What is the Multi-Agent Workforce Planner used for?

It is used to break down large software features into smaller, parallel tasks that can be executed by specialized AI agents simultaneously to speed up development.

Does it require other skills to function effectively?

It lists the product-requirements-designer skill as a prerequisite to ensure the input feature specifications are detailed enough for accurate decomposition.

Multi-Agent Workforce Planner

Name: Multi-Agent Workforce Planner
Author: organvm-iv-taxis

byorganvm-iv-taxis

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Productivity & Workflow

Decomposes complex feature requirements into optimized, parallelized workstreams for specialized AI agents.

The Multi-Agent Workforce Planner is an advanced orchestration skill designed to scale AI development by breaking down massive feature sets into manageable, parallel tracks. It meticulously analyzes task dependencies, assigns specialized roles—Explore, Plan, Bash, and Edit—to different agent instances, and constructs a robust execution roadmap. By identifying parallelization opportunities and implementing failure recovery protocols, this skill allows developers to maximize throughput on large-scale implementations while maintaining architectural consistency and managing complex cross-file dependencies.

Key Features

01Automated dependency graph generation for complex feature sets

02Specialized agent role assignment (Explore, Plan, Bash, Edit)

032 GitHub stars

04Strategic parallelization including horizontal and vertical tracks

05Comprehensive progress tracking with visual status reporting

06Robust failure recovery, retry logic, and checkpointing

Use Cases

01Scaling large-scale feature implementations across multiple repositories or files

02Optimizing development throughput via interface-first parallelization strategies

03Coordinating specialized AI agents for complex full-stack development tasks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add organvm-iv-taxis/a-i--skills multi-agent-workforce-planner

For use in Claude.ai and ChatGPT

Download Skill