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designing-workflow-skills

Guide workflow-based AI skill design with routing, pipelines, and safety gates.

1|Updated Jul 20, 2022
Search Tags:#quality assurance#llm development#progressive disclosure#skill architecture#workflow patterns#ai skill design
One-click install
npx skills add https://github.com/fruch/coodie --skill designing-workflow-skills-fruch
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: designing-workflow-skills
Source: https://github.com/fruch/coodie/tree/main/.github/skills/designing-workflow-skills
Command: npx skills add https://github.com/fruch/coodie --skill designing-workflow-skills-fruch

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive framework and best practices for designing, structuring, and reviewing workflow-based AI skills, ensuring reliability, maintainability, and adherence to best practices.

Core Features & Use Cases

  • Structured Design Guidance: Offers patterns (Routing, Sequential Pipeline, Linear Progression, Safety Gate, Task-Driven) for organizing complex AI tasks.
  • Content Organization: Enforces progressive disclosure, splitting content between SKILL.md, references/, and workflows/ to maintain LLM focus.
  • Quality Assurance: Provides detailed checklists and anti-pattern catalogs for self-review and ensuring skill robustness.
  • Use Case: When developing a new AI skill that involves multiple steps, decision points, or requires user interaction, use this Skill to guide the architecture and ensure it's built according to established quality standards.

Quick Start

Use the designing-workflow-skills to get guidance on structuring a new AI skill.

Frequently Asked Questions about designing-workflow-skills

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

FAQPage Schema
How do I structure a multi-step AI workflow to maintain LLM focus?▼

Organize multi-step AI workflows using progressive disclosure, splitting content between SKILL.md, references, and workflow directories to maintain LLM focus and ensure reliability.

What are the best architectural patterns for designing complex AI skills?▼

Best architectural patterns for complex AI skills include routing, sequential pipelines, linear progression, safety gates, and task-driven structures to ensure robust and maintainable operations.

How do I ensure quality assurance when developing AI workflow skills?▼

Ensure quality assurance in AI workflow development by applying detailed checklists and anti-pattern catalogs during self-review to verify robustness, maintainability, and adherence to best practices.

When should I use safety gates in an AI workflow pipeline?▼

Use safety gates in AI workflow pipelines when your multi-step process involves critical decision points or requires user interaction, ensuring reliable execution and preventing unsafe actions.

What are common anti-patterns to avoid when building AI skill architectures?▼

Common anti-patterns in AI skill architecture include failing to enforce progressive disclosure, overloading LLM context with unstructured content, and skipping quality assurance checklists during development.

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