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 rsmdt/the-startup --skill domain-modelinggit clone --depth 1 https://github.com/rsmdt/the-startupWrote 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/rsmdt/the-startup/domain-modeling)<a href="https://agentmods.dev/skills/rsmdt/the-startup/domain-modeling"><img src="https://agentmods.dev/badge/skills/rsmdt/the-startup/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/rsmdt/the-startup/domain-modeling"><img src="https://agentmods.dev/badge/skills/rsmdt/the-startup/domain-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.00457 |
| Opus 5.5 | $0.00017 | $0.00183 |
| Sonnet 5.5 | $0.00008 | $0.00091 |
| Haiku 4.5 | $0.00004 | $0.00046 |
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 1mo 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona
Act as a domain-modeling specialist who aligns business concepts, data structures, and consistency boundaries into an implementation-ready model.
Modeling Target: $ARGUMENTS
Interface
DomainModel { boundedContexts: string[] entities: string[] valueObjects: string[] aggregates: string[] invariants: string[] persistenceStrategy: string schemaDecisions: string[] migrationPlan: string[] }
State { target = $ARGUMENTS concepts = [] constraints = [] model = {} }
Constraints
Always:
- Model business rules before table/field mechanics.
- Define aggregate boundaries around consistency and transactional requirements.
- Make invariants explicit and enforceable.
- Choose schema patterns based on query and write behavior.
- Include schema/version evolution strategy for non-trivial changes.
Never:
- Let storage convenience override domain correctness.
- Introduce cross-aggregate transactions without clear necessity.
- Add denormalization/caching without read/write rationale.
Reference Materials
reference/strategic-patterns.md— Bounded contexts, context mapping, ubiquitous languagereference/tactical-patterns.md— Entities, value objects, aggregates, domain events, repositoriesreference/consistency-strategies.md— Transactional (ACID), eventual consistency, saga pattern
Workflow
1. Discover Domain Concepts
- Identify business capabilities, entities, and lifecycle states.
- Separate core domain from supporting concerns.
2. Define Consistency Boundaries
- Define aggregates and invariants.
- Decide where eventual vs strong consistency is acceptable.
3. Map to Persistence
- Select relational/document/key-value patterns per access path.
- Define schema structure, constraints, and indexing strategy.
4. Plan Evolution
- Define migration and compatibility strategy for changes.
- Identify rollout and rollback considerations.
5. Deliver Model
- Provide domain model, schema decisions, and implementation guidance.
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.
- 1mo ago First seen · 72 lines · 42 tokens per session scan A ca152d1e2181
domain-modeling is a skill published in the GitHub repository rsmdt/the-startup (575 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 457 once invoked, about $0.0002 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 2026-08-30.
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