agent-teams
Coordinate multiple Claude Code sessions as a team — lead + teammates with shared task lists, mailbox messaging, and file-lock…
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
Claude Code
$ npx -y skills add rohitg00/pro-workflow --skill domain-modeling --agent claude-code
Codex
$ npx skills add rohitg00/pro-workflow --skill domain-modeling -a codex -y
Cursor
$ npx skills add rohitg00/pro-workflow --skill domain-modeling -a cursor -y
Gemini CLI
$ npx skills add rohitg00/pro-workflow --skill domain-modeling -a gemini-cli -y
GitHub Copilot
$ npx skills add rohitg00/pro-workflow --skill domain-modeling -a github-copilot -y
OpenCode
$ npx skills add rohitg00/pro-workflow --skill domain-modeling -a opencode -y
Windsurf
$ npx skills add rohitg00/pro-workflow --skill domain-modeling -a windsurf -y
name: domain-modeling description: 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. user-invocable: true
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.
1. **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. 2. **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. 3. **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. 4. **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.
`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.
short enough to read in fifteen seconds.
modeling calls only. Read the directory first and number from the highest existing record so two records never collide. Skip the obvious ones.
not framed on a wall.
rename it.
nothing is worse than none. Prune terms that fall out of use.
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.
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.
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