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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/tudeorangbiasa-domain-modeling
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/domain-modeling
What's inside
- Skill name
domain-modeling- Description
- Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
- License
- MIT
- Instructions
- 73 lines in SKILL.md · view on GitHub
Files (5)
- ADR-FORMAT.md
- CREDITS.md
- GLOSSARY-FORMAT.md
- SKILL.md
- openai.yaml · agents/
SKILL.md (first lines)
# 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/ ``` Legacy names: a repo that still carries `CONTEXT.md` (or a `CONTEXT-MAP.md`) means the same glossary under the old name. Read and update that file instead of creating a `GLOSSARY.md` beside it. Never keep both names for one glossary. 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-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: 1. **Hard to reverse**: the cost of changing your mind later is meaningful 2. **Surprising without context**: a future reader will wonder "why did they do it this way?" 3. **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](./ADR-FORMAT.md).
From TudeOrangBiasa/skills-for-agents, MIT.
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show-me-your-work
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Keep a reviewable decision trail for long or unattended work: TSV log per decision, end audit, cross-model attention flags.
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setup-pre-commit
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Set up fast hooks with the repo's own toolchain (oxlint/oxfmt, Biome, or Prettier), type checking, tests, and a token-size gate.
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arena
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Parallel design bakeoff: N candidates on one brief, cross-judge, pick a base, graft the best parts.
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break
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Stress-test one component against worst-case content and states on a throwaway page, then report what visibly broke.
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correct
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Eliminate repeated agent mistakes at the highest level that works: architecture, types, lint, tests, docs last.
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architect
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Settle types, signatures, and module shape before code: ground, sketch twice, agree, implement, scrap when wrong.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
how
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Explain how a subsystem works: triage complexity, fan out explorers on 2 to 4 angles for complex scopes, synthesize into fixed sections.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
interrogate
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Adversarial multi-model review with rubric and bucketed verdict.
SkillAFreshness: A★ 1Claude Code +9 - 0.579score
no-comments
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Kill needless comments plus the dead code they protect, fix root causes in scope, encode real constraints as structure.
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prototype
TudeOrangBiasa
Build a throwaway prototype to answer a design question.
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
codebase-design
TudeOrangBiasa
Shared vocabulary for designing deep modules.
SkillAFreshness: A★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 1
- Last commit (this folder)
- Oct 5, 2026 (25 days ago)
- Last release
- Oct 23, 2026 (7 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from TudeOrangBiasa
- 0.592score
diagnose
TudeOrangBiasa
Diagnosis loop for hard bugs and performance regressions.
SkillAFreshness: A★ 1Claude Code +9 - 0.589score
show-me-your-work
TudeOrangBiasa
Keep a reviewable decision trail for long or unattended work: TSV log per decision, end audit, cross-model attention flags.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
break
TudeOrangBiasa
Stress-test one component against worst-case content and states on a throwaway page, then report what visibly broke.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
setup-pre-commit
TudeOrangBiasa
Set up fast hooks with the repo's own toolchain (oxlint/oxfmt, Biome, or Prettier), type checking, tests, and a token-size gate.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
arena
TudeOrangBiasa
Parallel design bakeoff: N candidates on one brief, cross-judge, pick a base, graft the best parts.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
interrogate
TudeOrangBiasa
Adversarial multi-model review with rubric and bucketed verdict.
SkillAFreshness: A★ 1Claude Code +9
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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
domain-modeling skill. Agent Mart. https://agentmart.dev/skills/tudeorangbiasa-domain-modeling (last updated 2026-10-24)