What is Always-On Guidance?

It is a specialized skill for Claude Code that enforces behavioral rules, tool usage standards, and model-specific defaults for agents working in a swarm environment.

Does this skill help with automated testing?

Yes, it mandates a strict Red-Green-Refactor testing discipline whenever tests cover the area being modified by the agent swarm.

How does it handle different AI models?

It provides tailored instructions for GPT-5.2-code, focusing on brevity and imperatives, and Opus 4.5, allowing for brief rationales and phased planning.

How does it prevent code conflicts in a swarm?

The skill enforces a file reservation system using time-to-live (TTL) locks to ensure only one agent edits a specific file at a time, releasing the lock upon task completion.

Always-On Swarm Guidance

Name: Always-On Swarm Guidance
Author: primeinc

byprimeinc

Productivity & Workflow

Enforces consistent behavior, tool protocols, and model-specific execution patterns across autonomous agent swarms.

About

Always-On Swarm Guidance provides a standardized operational framework for Claude-plugin agents operating within a multi-agent swarm architecture. It ensures seamless coordination by managing file reservations, subtask handoffs, and tool selection while optimizing output styles for specific model architectures like GPT-5.2-code and Opus 4.5. By implementing strict instruction priorities and testing disciplines, this skill minimizes errors in complex environments and ensures all agents adhere to the latest hive and swarm protocols while avoiding deprecated legacy references.

Key Features

Strict Instruction Priority Management
Universal Swarm Tool Integration (hive, swarm, hivemind)
Standardized Red-Green-Refactor Testing Discipline
Model-Specific Behavior Optimization for GPT and Opus
0 GitHub stars
Automated File Reservation and Conflict Prevention

Use Cases

Managing complex multi-agent workflows to prevent file conflicts during concurrent edits.
Optimizing agent response styles based on the specific strengths of the underlying LLM.
Standardizing testing and coordination protocols across automated software engineering tasks.

About

Key Features

Strict Instruction Priority Management
Universal Swarm Tool Integration (hive, swarm, hivemind)
Standardized Red-Green-Refactor Testing Discipline
Model-Specific Behavior Optimization for GPT and Opus
0 GitHub stars
Automated File Reservation and Conflict Prevention

Use Cases

Managing complex multi-agent workflows to prevent file conflicts during concurrent edits.
Optimizing agent response styles based on the specific strengths of the underlying LLM.
Standardizing testing and coordination protocols across automated software engineering tasks.