directives

Configure project.yaml, MCP settings, and quality gates for multi-agent teams.

2|Updated Oct 1, 2024
One-click install
npx skills add https://github.com/ZeiZel/dotfiles --skill directives
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: directives
Source: https://github.com/ZeiZel/dotfiles/tree/main/.claude/skills/directives
Command: npx skills add https://github.com/ZeiZel/dotfiles --skill directives

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Centralizes and enforces governance over agent directives, project configuration, quality gates, and context strategies to reduce drift and accelerate multi-agent collaboration.

Core Features & Use Cases

  • Unified configuration: manage project.yaml, MCP server settings, and policy templates from a single interface.
  • Quality and context governance: tune thresholds, capabilities, and context strategies for predictable AI behavior.
  • Use Case: when onboarding a new AI project, apply standardized policies and gates to ensure consistent setup.

Quick Start

Provide initial governance by populating docs/project.yaml with your project details and invoking the directive management workflow to apply settings.

Frequently Asked Questions about directives

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

FAQPage Schema
How do I centralize project policies and agent directives for multi-agent teams?

Centralize project policies and agent directives by configuring project.yaml, MCP server settings, and quality gates from a single interface to reduce drift and accelerate multi-agent collaboration across AI-assisted projects.

What are quality gates in AI-assisted projects and how do I configure them?

Quality gates are configurable thresholds and coding standards enforced through project.yaml and policy templates. You configure them to ensure predictable AI behavior and maintain consistent project governance across multi-agent teams.

How do I set up MCP server configurations for a new AI project?

Set up MCP server configurations by populating docs/project.yaml with your project details and invoking the directive management workflow to apply standardized policies, capabilities, and context strategies for consistent project onboarding.

Does this approach work for enforcing coding standards across multiple AI agents?

Yes, it works for enforcing coding standards by applying standardized policy templates and quality definitions to multi-agent teams, ensuring consistent setup and predictable AI behavior across the project lifecycle.

What is the best way to manage context strategies and capabilities for AI agents?

The best way to manage context strategies is through a unified configuration interface that tunes thresholds, capabilities, and context strategies, reducing drift and accelerating multi-agent collaboration across AI-assisted projects.