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Domain Modeling Agent Skill

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.

744 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
2755
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/rohitg00/pro-workflow --skill domain-modeling

The instruction itself

5 sections, as written by the author

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.

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How to use it

Copy the folder

Take rohitg00/domain-modeling from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.