Domain Modeling
Matt PocockCommunityCreated by Matt Pocock
- Skill
- Role or persona
- Software development
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The domain-modeling skill helps teams maintain a precise and consistent language within their codebase. It acts as a partner in architectural design, actively challenging ambiguous terminology, identifying contradictions between documentation and code, and facilitating the creation of Architecture Decision Records (ADRs) when significant trade-offs are made. It focuses on keeping the project's glossary accurate and free of implementation details while ensuring that documentation evolves alongside the system.
What it does
- Challenges conflicting terminology against the existing project glossary
- Proposes precise canonical terms to replace vague or overloaded language
- Stress-tests domain relationships using concrete edge-case scenarios
- Identifies contradictions between stated domain logic and actual code implementation
- Updates GLOSSARY.md files inline as terms are resolved
- Assists in drafting ADRs for decisions that are hard to reverse or require context
When to use it
- When defining or refining the core terminology of a software project
- When writing or updating a GLOSSARY.md file
- When recording or editing an Architecture Decision Record (ADR)
- When discussing domain boundaries and relationships during design sessions
Advantages
- Ensures consistent language across the development team
- Prevents technical debt caused by ambiguous or overloaded terms
- Maintains a clear separation between domain concepts and implementation details
- Provides a structured approach to documenting significant architectural trade-offs
Usage examples
- “We are discussing the billing module. Does an 'Account' refer to a Customer or a User?”
- The agent will analyze the current glossary and codebase to help distinguish between these concepts and propose a canonical term for each.
- “I want to document why we chose Postgres for our write model.”
- The agent will evaluate if the decision meets the criteria for an ADR and, if appropriate, guide you through drafting it using the standard format.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/mattpocock/domain-modeling/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip domain-modeling.zip -d .agents/skills
Documentation by Matt Pocock
Domain Modeling
Actively build and sharpen the project's domain model as you design. This is the active discipline: challenging terms, inventing edge-case scenarios, and writing the glossary and decisions down the moment they crystallise. (Merely reading GLOSSARY.md for vocabulary is not this skill: that's a one-line habit any skill can do. This skill is for when you're changing the model, not just consuming it.)
File structure
Most repos have a single context:
/
├── GLOSSARY.md
├── docs/
│ └── adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/If a GLOSSARY-MAP.md exists at the root, the repo has multiple contexts. The map points to where each one lives:
/
├── GLOSSARY-MAP.md
├── docs/
│ └── adr/ ← system-wide decisions
├── src/
│ ├── ordering/
│ │ ├── GLOSSARY.md
│ │ └── docs/adr/ ← context-specific decisions
│ └── billing/
│ ├── GLOSSARY.md
│ └── docs/adr/Create files lazily: only when you have something to write. If no GLOSSARY.md exists, create one when the first term is resolved. If no docs/adr/ exists, create it when the first ADR is needed.
During the session
Challenge against the glossary
When the user uses a term that conflicts with the existing language in GLOSSARY.md, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y. Which is it?"
Sharpen fuzzy language
When the user uses vague or overloaded terms, propose a precise canonical term. "You're saying 'account': do you mean the Customer or the User? Those are different things."
Discuss concrete scenarios
When domain relationships are being discussed, stress-test them with specific scenarios. Invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts.
Cross-reference with code
When the user states how something works, check whether the code agrees. If you find a contradiction, surface it: "Your code cancels entire Orders, but you just said partial cancellation is possible. Which is right?"
Update GLOSSARY.md inline
When a term is resolved, update GLOSSARY.md right there. Don't batch these up: capture them as they happen. Use the format in GLOSSARY-FORMAT.md.
GLOSSARY.md should be totally devoid of implementation details. Do not treat GLOSSARY.md as a spec, a scratch pad, or a repository for implementation decisions. It is a glossary and nothing else.
Offer ADRs sparingly
Only offer to create an ADR when all three are true:
Hard to reverse: the cost of changing your mind later is meaningful
Surprising without context: a future reader will wonder "why did they do it this way?"
The result of a real trade-off: there were genuine alternatives and you picked one for specific reasons
If any of the three is missing, skip the ADR. Use the format in ADR-FORMAT.md.
Files
- ADR-FORMAT.md2.7 KiB
- ATTRIBUTION.mdAdded by AutoGineer871 B
- GLOSSARY-FORMAT.md2.2 KiB
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md3.3 KiB
- agents/openai.yaml101 B
ADR-FORMAT.md
ADR Format
ADRs live in docs/adr/ and use sequential numbering: 0001-slug.md, 0002-slug.md, etc.
Create the docs/adr/ directory lazily: only when the first ADR is needed.
Template
# {Short title of the decision}
{1-3 sentences: what's the context, what did we decide, and why.}That's it. An ADR can be a single paragraph. The value is in recording that a decision was made and why, not in filling out sections.
Optional sections
Only include these when they add genuine value. Most ADRs won't need them.
Status frontmatter (
proposed | accepted | deprecated | superseded by ADR-NNNN): useful when decisions are revisitedConsidered Options: only when the rejected alternatives are worth remembering
Consequences: only when non-obvious downstream effects need to be called out
Numbering
Scan docs/adr/ for the highest existing number and increment by one.
When to offer an ADR
All three of these must be true:
Hard to reverse: the cost of changing your mind later is meaningful
Surprising without context: a future reader will look at the code and wonder "why on earth did they do it this way?"
The result of a real trade-off: there were genuine alternatives and you picked one for specific reasons
If a decision is easy to reverse, skip it: you'll just reverse it. If it's not surprising, nobody will wonder why. If there was no real alternative, there's nothing to record beyond "we did the obvious thing."
What qualifies
Architectural shape. "We're using a monorepo." "The write model is event-sourced, the read model is projected into Postgres."
Integration patterns between contexts. "Ordering and Billing communicate via domain events, not synchronous HTTP."
Technology choices that carry lock-in. Database, message bus, auth provider, deployment target. Not every library: just the ones that would take a quarter to swap out.
Boundary and scope decisions. "Customer data is owned by the Customer context; other contexts reference it by ID only." The explicit no-s are as valuable as the yes-s.
Deliberate deviations from the obvious path. "We're using manual SQL instead of an ORM because X." Anything where a reasonable reader would assume the opposite. These stop the next engineer from "fixing" something that was deliberate.
Constraints not visible in the code. "We can't use AWS because of compliance requirements." "Response times must be under 200ms because of the partner API contract."
Rejected alternatives when the rejection is non-obvious. If you considered GraphQL and picked REST for subtle reasons, record it; otherwise someone will suggest GraphQL again in six months.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
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Attribution and licence
- Created by
- Matt Pocock
- Publisher
- Matt Pocock (Community)
- Source
- mattpocock/skills · skills/engineering/domain-modeling · commit 4ae2317
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Matt Pocock.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download domain-modeling.zip