Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add int2t05/engineering-skills --skill domain-modelinggit clone --depth 1 https://github.com/int2t05/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/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<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="Reviewed on agentmods" width="80" 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 | $0.00028 | $0.00311 |
| Opus 5.5 | $0.00011 | $0.00124 |
| Sonnet 5.5 | $0.00006 | $0.00062 |
| Haiku 4.5 | $0.00003 | $0.00031 |
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 8d 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.
What it actually says
Domain Modeling
When to use
- Clarify domain terms, invariants and ownership from real scenarios.
Not for: schema-design for storage; architecture for system boundaries.
Steps
-
Read existing terminology, requirements, code and decisions; identify ambiguous concepts.
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Test terms against normal and exceptional scenarios, specifying invariants and state transitions rather than extracting nouns into entities.
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Resolve business ambiguity with the user and update the glossary and affected approved descriptions consistently.
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Record only consequential decisions separately; give examples distinguishing similar concepts.
Output: Suggested paths, subject to human audit: CONTEXT.md; optionally docs/design/adr/NNNN-slug.md.
Verify
- Terms explain actual scenarios and invariants; glossary and implementation agree or discrepancies are explicit.
References
- engineering-principles.md — shared decision boundaries, scope and verification.
- human-audit.md — document consent, readability and human review.
- references/context-format.md — CONTEXT.md structure, rules, single vs multi-context repos
- references/adr-format.md — ADR template, numbering, what qualifies as an ADR-worthy decision
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.
- 8d ago Changed · -58 lines · -41 tokens per session f4d99da41e6b
- 15d ago Changed · +4 lines af598f28a393
- 1mo 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 9d ago), licensed MIT. It adds 28 tokens to every session and 311 once invoked, about $0.0001 per session on Opus 5.5. 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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