Domain modeling

Skill rohitg00/pro-workflow/skills/domain-modeling

Claude Code learns from your corrections: self-correcting memory that compounds over 50+ sessions. Context engineering, parallel worktrees, agent teams, and 17 battle-tested skills.

Install

npx -y skills add rohitg00/pro-workflow --skill domain-modeling

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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What its author says it does

Copied from the file, not written here

Build the project's shared language and bounded contexts before writing code, so names stay consistent and the agent stops paraphrasing domain concepts. Produces a CONTEXT.md glossary and decision records. Use at the start of a project or feature, or when the codebase and the people describing it speak different languages.

SKILL.md

2.9 KB, as published. Nobody here has run it

domain-modeling

Most misbuilds start as a language gap: the agent is dropped into a project and left to infer the jargon, so it uses twenty words where the domain has one. A shared language closes the gap. When code, conversation, and the model all draw from the same vocabulary, names line up, navigation gets cheaper, and the model spends fewer tokens reasoning because it has a tighter language to reason in.

Method

Harvest the terms. From the request, the codebase, and the user's own words, list the nouns and verbs that carry domain meaning - the concepts a newcomer would have to ask about. Prefer the user's word over a synonym you like better.
Pin each one. Write a one-line definition in the project's own language, not a dictionary definition. If two terms blur together, force the distinction or collapse them - ambiguity here becomes inconsistent names in code.
Draw the boundaries. Where the same word means different things in different parts of the system, that is a boundary. Name each context and note which terms belong to it. A term that means two things is two terms.
Record the hard calls. When a modeling choice was contested or will be questioned later, write a short decision record: context, choice, alternatives rejected, why.

Outputs

CONTEXT.md - the shared-language glossary. One term per line: term - what it means in this project. Grouped by bounded context when there is more than one. Point every future session at this file. On re-run, add new terms and update definitions that changed; do not rewrite the file wholesale.
Bounded-context sketch - the contexts and which terms live in each, short enough to read in fifteen seconds.
Decision records in docs/decisions/NNNN-slug.md for the contested modeling calls only. Read the directory first and number from the highest existing record so two records never collide. Skip the obvious ones.

Guardrails

The glossary is for the model as much as the human - write it to be loaded, not framed on a wall.
Do not invent terms the project does not use. Reflect the domain; do not rename it.
Keep it small and current. A glossary that lists everything and updates nothing is worse than none. Prune terms that fall out of use.

Where it fits

Run this before plan-interrogate on a new area, or let plan-interrogate call back here when it hits terms it cannot pin. The CONTEXT.md this produces is the same file plan-interrogate emits - one shared-language artifact, two ways in.