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skailup-prog-expert-skill-system

Design and implement LLM agent skill systems with artifacts, gates, and UI integration.

Updated Mar 28, 2026
Search Tags:#patterns#orchestration#pipeline#artifact#cross-references#ui-integration#skill-system
One-click install
npx skills add https://github.com/skaile-ai/ai-assets --skill skailup-prog-expert-skill-system
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skailup-prog-expert-skill-system
Source: https://github.com/skaile-ai/ai-assets/tree/main/dev-implementation-experts-js/skills/skailup-prog-expert-skill-system
Command: npx skills add https://github.com/skaile-ai/ai-assets --skill skailup-prog-expert-skill-system

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Designs and governs end-to-end LLM agent skill systems by enabling artifact-driven pipelines, gating, cross-reference management, and UI integration.

Core Features & Use Cases

  • Artifact-first pipelines: artifacts are the source of truth and drive all steps.
  • Gate-driven execution: deterministic file-existence checks guard progress.
  • Cross-reference discipline: bidirectional linking to maintain Referential integrity.
  • UI integration: patterns and contracts for browser-based tooling and onboarding.
  • Pattern governance: encompasses five-layer architecture, recipes, and references for scalable design.

Quick Start

Follow this workflow to design and implement an expert-level skill system: define artifact folders, create canonical SKILL.md templates for each skill, and wire an orchestrator-driven pipeline.

Frequently Asked Questions about skailup-prog-expert-skill-system

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

FAQPage Schema
How do I design an artifact-driven pipeline for LLM agent skill systems?▼

An artifact-driven pipeline uses artifacts as the source of truth to drive all execution steps. You define artifact folders for inputs and outputs, then create canonical SKILL.md templates with frontmatter contracts to establish the workflow.

What are pipeline gates and how do they govern multi-skill execution?▼

Pipeline gates are deterministic file-existence checks defined in pipeline.json that guard progress. They ensure required artifacts exist before allowing downstream skills to execute, preventing incomplete state transitions in multi-skill pipelines.

How do I maintain referential integrity with cross-references across multiple LLM skills?▼

Cross-reference discipline maintains referential integrity through bidirectional linking between artifacts. This ensures that when an artifact is updated or moved, all dependent references across the multi-skill pipeline remain synchronized and valid.

Can I use frontmatter contracts to wire UI integration for browser-based LLM tooling?▼

Yes, frontmatter contracts define patterns and protocols for UI integration. They specify how browser-based tooling interfaces with the skill system, enabling onboarding and artifact visualization through structured metadata agreements.

What is the best way to structure a five-layer architecture for scalable skill pattern governance?▼

A five-layer architecture for skill pattern governance uses recipes, reference implementations, and canonical templates to guide scalable design. It separates orchestration, artifact processing, gating, cross-references, and UI integration into distinct structural layers.

Do I need reference implementations to create canonical SKILL.md templates for an orchestrator-driven pipeline?▼

Yes, reference implementations guide development by providing concrete examples of artifact workflows and gating logic. They demonstrate how canonical SKILL.md templates and frontmatter contracts function within an orchestrator-driven pipeline.

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