_shared

Define shared conventions for spec-driven development artifacts and workflows.

Updated Jun 5, 2026
One-click install
npx skills add https://github.com/zMynxx/bifrost-with-opencode --skill shared-zmynxx
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: _shared
Source: https://github.com/zMynxx/bifrost-with-opencode/tree/main/.opencode/skills/_shared
Command: npx skills add https://github.com/zMynxx/bifrost-with-opencode --skill shared-zmynxx

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides shared documentation and conventions that keep spec-driven development workflows consistent across related skills without acting as a standalone user command.

Core Features & Use Cases

  • Shared SDD References: Defines common protocols for artifact persistence, OpenSpec structures, status handling, and phase execution.
  • Workflow Consistency: Supplies reusable guidance for orchestrators and phase skills that need aligned naming, recovery, and collaboration rules.
  • Use Case: Supports AI development teams building repeatable SDD pipelines where multiple skills need to read and write compatible artifacts.

Quick Start

Use the shared references skill documentation to understand the conventions required by the SDD skills in this repository.

Frequently Asked Questions about _shared

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

FAQPage Schema
What are spec-driven development workflows in AI coding?

Spec-driven development (SDD) workflows coordinate AI coding skills using shared conventions for artifact persistence, OpenSpec structures, and phase execution to maintain consistency across software engineering pipelines.

How do I standardize artifact naming conventions across multiple AI development skills?

Standardize artifact naming by implementing shared technical requirements for consistent naming, recovery protocols, execution boundaries, and status contracts across all orchestrated SDD phase skills.

How do you coordinate OpenSpec structures and memory persistence for AI agents?

Coordinate OpenSpec structures and memory persistence by defining common protocols for status handling and artifact management that allow multiple AI skills to read and write compatible artifacts.

Can I use this Skill as a standalone command to run SDD phases?

No, this Skill provides shared documentation and conventions rather than acting as a standalone user command. It supplies reusable guidance for orchestrators and phase skills requiring aligned collaboration rules.

What are the limitations of using shared conventions for AI skill orchestration?

The limitation is that shared SDD conventions require related phase skills to explicitly adopt the defined execution boundaries and recovery protocols to achieve workflow consistency and compatible artifact generation.