feature-domain-expert

Author and consume feature-level domain knowledge files in ai-context/features/.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/fearovex/claude-config --skill feature-domain-expert
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feature-domain-expert
Source: https://github.com/fearovex/claude-config/tree/main/skills/feature-domain-expert
Command: npx skills add https://github.com/fearovex/claude-config --skill feature-domain-expert

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Authoring and consuming feature-level domain knowledge files in ai-context/features/. Reference guide for bounded-context business rules, invariants, integration points, and known gotchas.

Core Features & Use Cases

  • Author and consume feature-level domain knowledge files in ai-context/features/, providing a stable knowledge base for SDD cycles.
  • Enforce a canonical structure for feature knowledge to guide SDD proposals, specs, and designs.
  • Preserve long-lived domain rules across changes by separating domain knowledge from per-change delta specs.

Quick Start

Create or update ai-context/features/feature-domain-expert.md with the canonical six sections to enable discovery and tooling.

Frequently Asked Questions about feature-domain-expert

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

FAQPage Schema
How do I preserve bounded-context domain knowledge for SDD phases?▼

You preserve bounded-context domain knowledge for SDD by authoring feature-level files that separate long-lived business rules from per-change delta specs. This keeps domain knowledge stable across propose, spec, design, and verify phases.

What is the canonical structure for feature domain knowledge files?▼

The canonical structure for feature domain knowledge files requires a six-section format in ai-context/features/feature-domain-expert.md. It must include a frontmatter header with name and description to enable discovery and tooling.

How do I separate domain knowledge from per-change delta specs?▼

You separate domain knowledge from per-change delta specs by maintaining stable feature-level files in ai-context/features/. This approach stores business rules, invariants, and integration points independently from individual change specifications.

When do I need to update feature-level domain knowledge files?▼

You need to update feature-level domain knowledge files when creating or modifying bounded-context features to guide SDD phases. This ensures long-lasting rules, integration points, and known gotchas remain accurate across changes.

Does the feature-domain-expert file format require frontmatter for discovery?▼

Yes, the feature-domain-expert file format requires a frontmatter header containing name and description for discovery and tooling. This header accompanies the canonical six-section structure within the ai-context/features/ directory.