Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add int2t05/engineering-skills/plugin install engineering-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/int2t05/engineering-skills/domain-modeling)<a href="https://agentmods.dev/skills/int2t05/engineering-skills/domain-modeling"><img src="https://agentmods.dev/badge/skills/int2t05/engineering-skills/domain-modeling.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.01094 |
| Opus 5 | $0.00034 | $0.00547 |
| Sonnet 5 | $0.00014 | $0.00219 |
| Haiku 4.5 | $0.00007 | $0.00109 |
Grade A, and why
domain-modeling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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. This skill is for when you're changing the model.
When to use
- Pinning down domain terminology or establishing a ubiquitous language
- A term the user uses conflicts with the existing
CONTEXT.mdglossary - Stress-testing domain relationships against concrete edge-case scenarios
- Recording an architectural decision that is hard to reverse, surprising, or a real trade-off
- Another skill needs to maintain or update the domain model
- Triggers on "domain model", "ubiquitous language", "CONTEXT.md", "ADR", "领域模型", "统一语言", "领域建模"
Not for: merely reading CONTEXT.md for vocabulary — that's a habit any skill can do; this
skill is for when you're changing the model. NOT for greenfield system architecture (use
architecture).
Steps
1. Locate the context
Most repos have a single CONTEXT.md at the root. If a CONTEXT-MAP.md exists, the repo has
multiple contexts — read it to find which context the current topic relates to. If neither exists,
create a root CONTEXT.md lazily when the first term is resolved. Create docs/design/adr/
lazily when the first ADR is needed.
2. Challenge terms against the glossary
When the user uses a term that conflicts with the existing language in CONTEXT.md, call it out
immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"
When terms are vague or overloaded, propose a precise canonical term. "You're saying 'account' — do you mean the Customer or the User? Those are different things."
3. Stress-test with concrete scenarios
When domain relationships are being discussed, invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts. The awkward cases — the happy path, a tricky edge case, an attempt at something that should be illegal — are where the model breaks.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 90 lines · 69 tokens per session scan A a97b8a1c0da5
domain-modeling is a skill published in the GitHub repository int2t05/engineering-skills (3 stars, last pushed 7d ago), licensed MIT. It adds 69 tokens to every session and 1,094 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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