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 denyszhak/pystack-skills --skill python-pure-domain-layergit clone --depth 1 https://github.com/denyszhak/pystack-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/denyszhak/pystack-skills/python-pure-domain-layer)<a href="https://agentmods.dev/skills/denyszhak/pystack-skills/python-pure-domain-layer"><img src="https://agentmods.dev/badge/skills/denyszhak/pystack-skills/python-pure-domain-layer/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/denyszhak/pystack-skills/python-pure-domain-layer"><img src="https://agentmods.dev/badge/skills/denyszhak/pystack-skills/python-pure-domain-layer.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 | $0.00193 | $0.03617 |
| Opus 5.5 | $0.00077 | $0.01447 |
| Sonnet 5.5 | $0.00039 | $0.00723 |
| Haiku 4.5 | $0.00019 | $0.00362 |
Grade A, and why
python-pure-domain-layer 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 — 428 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pure domain layer (Cosmic Python style)
This is the opt-in alternative to python-aggregate-and-repo. The default style (SA model with behavior) is faster to write and read; this style adds boilerplate in exchange for a domain that knows nothing about SQLAlchemy. Switch to this when:
- Your invariants are dense enough that you want sub-millisecond unit tests without a DB
- You expect the persistence story to change (Postgres → DynamoDB; or microservice → event-sourced)
- You have multiple persistence shapes for the same aggregate (write store + read store)
- You want the domain to be portable across services without dragging SA along
The cost: every aggregate exists in two places (the pure app/domain/<x>.py and the SA app/models/<x>.py), with translation methods (from_domain / to_domain) bridging them. That's real boilerplate. It pays back when invariants justify it.
This skill encodes the Cosmic Python pattern, modernized for Python 3.12+ typing.
Relationship to the default skill
python-aggregate-and-repo (the default) and this skill are two points on the same tradeoff curve, both legitimate. The default trades strict framework-freedom for less code. This skill trades more boilerplate for a domain that knows nothing about SQLAlchemy.
Context worth knowing: When Cosmic Python was written (2020), the alternative to imperative mapping was untyped classic-style declarative — genuinely worse than pure domain. SA 2.0's typed Mapped[] style narrowed that gap considerably; class Order(Base): id: Mapped[UUID] = mapped_column(primary_key=True) is type-safe and unobtrusive. Whether that narrowing changes the calculus for your project depends on how dense your invariants are. Pick this skill when you want a domain that's truly framework-free; pick the default when the translation boilerplate would outweigh the gain.
Both choices are correct for their contexts.
When to use this skill
- The codebase already has
app/domain/(this is the strong signal) - You're starting a system with rich business invariants (insurance pricing, financial settlement, multi-step fulfillment)
- You want pure-Python aggregate tests that run in microseconds
What ships with it
1 file 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 · 428 lines · 193 tokens per session scan A 7c4c2ea39ca9
python-pure-domain-layer is a skill published in the GitHub repository denyszhak/pystack-skills (4 stars, last pushed 5mo ago), licensed MIT. It adds 193 tokens to every session and 3,617 once invoked, about $0.0008 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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