Does this skill actually implement code changes?

No, this skill is restricted to producing planning artifacts. It creates the roadmap and metadata necessary for other agents to perform the actual implementation safely.

How does it prevent agents from overwriting each other's work?

It uses 'wave' grouping and 'conflict_group' logic to ensure that tasks modifying the same files or directories are never scheduled in the same execution wave.

Is it compatible with standard repository structures?

While it can be adapted, it is specifically optimized for the Autolab ecosystem, relying on .autolab state files, verifier policies, and iteration artifacts.

What is the primary purpose of the Swarm Planner?

Swarm Planner is designed to break down complex coding tasks into organized, dependency-aware plans that multiple AI agents can execute simultaneously without conflict.

Swarm Implementation Planner

Name: Swarm Implementation Planner
Author: mjenrungrot

bymjenrungrot

0•

Productivity & Workflow

Generates dependency-aware implementation plans optimized for parallel multi-agent execution within the Autolab ecosystem.

The Swarm Planner is a high-precision orchestration skill designed to architect complex development tasks into atomic, parallelizable units. It meticulously analyzes repository state, verifier policies, and stage-specific prompts to produce high-fidelity implementation plans that prevent file-write conflicts and ensure logical execution order. By organizing tasks into execution 'waves' and mapping explicit dependencies, it enables seamless multi-agent collaboration and large-scale project automation while maintaining strict safety boundaries.

Key Features

010 GitHub stars

02Subagent review pass for identifying dependency gaps and validation holes

03Parallel execution wave grouping to eliminate file-touch overlaps

04Machine-readable plan metadata generation for automated tracking

05Automatic dependency graph generation with ASCII visualization

06Scope validation against allowed edit directories and verifier policies

Use Cases

01Architecting large-scale refactors for parallel AI agent execution

02Resolving circular dependencies and race conditions in multi-agent workflows

03Creating structured implementation roadmaps for complex feature additions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add mjenrungrot/autolab swarm-planner

For use in Claude.ai and ChatGPT

Download Skill