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 perniemann/pnCore --skill pn-backend-architecturegit clone --depth 1 https://github.com/perniemann/pnCoreWrote 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/perniemann/pncore/pn-backend-architecture)<a href="https://agentmods.dev/skills/perniemann/pncore/pn-backend-architecture"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-backend-architecture/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/perniemann/pncore/pn-backend-architecture"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-backend-architecture.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 | $0.00037 | $0.01569 |
| Opus 5.5 | $0.00015 | $0.00628 |
| Sonnet 5.5 | $0.00007 | $0.00314 |
| Haiku 4.5 | $0.00004 | $0.00157 |
Grade A, and why
pn-backend-architecture 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Backend architecture
When to use
- Designing API structure or database schema before implementation begins.
- Choosing between service patterns (monolith, modular monolith, microservices).
- Schema design, indexing strategy, and performance considerations.
- Event-driven architecture, queuing, and async processing decisions.
- Cloud infrastructure and deployment strategy.
Workflow
1. Clarify requirements first
Before choosing a pattern, establish constraints:
- Scale: Expected traffic (requests/sec), data volume (rows, GB), and growth trajectory.
- Consistency: Does stale data break user trust, or is eventual consistency acceptable?
- Latency: Are there hard SLA requirements? (< 100ms p99, real-time sync, etc.)
- Team size: More services = more operational overhead. A team of 2 should not run 10 microservices.
- Deployment target: Managed cloud (Vercel, Railway, Render), containers (Fly, ECS), or bare metal?
2. Choose a service decomposition strategy
Start with a modular monolith. Extract services only when a specific boundary causes a measurable problem.
| Pattern | When to use | Risks |
|---|---|---|
| Monolith | < 5-person team, single domain, proving the product | Hard to scale individual bottlenecks |
| Modular monolith | Clear domain boundaries, single team, shared DB acceptable | Discipline required to maintain boundaries |
| Microservices | Independent scaling needs, separate deploy cadences, multiple teams | Network overhead, distributed tracing, operational complexity |
| Event-driven | Decoupled workflows (email on signup, inventory on order), async side effects | Eventual consistency, harder to debug |
Rules for extraction:
- Extract a service only when: a team boundary, a scaling need, or a technology requirement demands it.
- Never decompose by technical layer (separate service for "the DB layer"). Decompose by domain.
3. API contract design
Design the API contract before writing implementation code. Use OpenAPI-first.
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 · 151 lines · 37 tokens per session scan A ccb6fe4cf9f0
pn-backend-architecture is a skill published in the GitHub repository perniemann/pnCore (0 stars, last pushed 4d ago), licensed MIT. It adds 37 tokens to every session and 1,569 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 2026-09-03.
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