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AI EngineeringPython

Domain Modeling

by stevesolun

Domain Modeling is an AI Engineering skill for Claude Code, published by stevesolun in ctx.

578 stars71 forkson stevesolun/ctxAdded 2026/08/25+1% in starsRepository updated 2026/08/24
agentsai-agentsanthropicautomationclaudeclaude-codecontext-managementdeveloper-toolsharnessknowledge-graphllmllm-wikimcpmicro-skillsobsidianreal-timerecommendation-engineskill-managementskillswiki
Install in seconds
Install Domain Modeling
Copy Domain Modeling into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/stevesolun/ctx/tree/main/.agents/skills/domain-modeling ~/.claude/skills/domain-modeling

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/stevesolun/ctx.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
.agents/skills/domain-modeling/SKILL.md in stevesolun/ctx
Installs to
~/.claude/skills/domain-modeling
Collection
One of 25 skills cataloged from this repository
Category
AI Engineering2451 skills

What Domain Modeling does

Domain Modeling clarifies concepts, language, boundaries, and architectural decisions when terminology is ambiguous or a design depends on shared understanding. It helps you compare terms, test edge cases, and record durable definitions or ADRs when needed.

Domain Modeling is cataloged under AI Engineering on DirSkills. Domain Modeling comes from a repository tagged agents, ai-agents, anthropic, automation and claude.

Documentation

README

Model the domain

Build a precise shared understanding of the concepts that matter to the current decision. Read existing glossaries, context maps, ADRs, code, and tests when they provide relevant evidence.

Sharpen the model

  • Identify overloaded terms, hidden distinctions, and conflicting definitions.
  • Use concrete scenarios and edge cases to test whether concepts and boundaries hold.
  • Compare the stated model with behavior in the code and surface material contradictions.
  • Propose clear language when ambiguity is blocking progress, while respecting established repository terminology that remains accurate.

Ask the user to resolve a term only when their intent cannot be inferred safely and the distinction affects the outcome.

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Domain Modeling

  • What else does stevesolun publish alongside Domain Modeling?

    Domain Modeling is one of 25 skills that DirSkills catalogs from stevesolun/ctx, the repository it ships in. Its siblings there include Ask Matt, Code Review and Codebase Design. Each one is a separate skill with its own page in this directory, installs the same way Domain Modeling does, and is maintained by stevesolun in that same repository. The rest of the collection is listed on the stevesolun/ctx page.

  • How does Domain Modeling compare to other AI Engineering skills?

    Domain Modeling ranks #1984 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Domain Modeling against them. Open each page to compare what they document and how they install.

More from stevesolun/ctx

Domain Modeling is one of 25 skills cataloged on DirSkills from stevesolun/ctx.

See all 25 skills