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 AhmedHabiba/architor --skill architecture-patternsgit clone --depth 1 https://github.com/AhmedHabiba/architorWrote 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/ahmedhabiba/architor/architecture-patterns)<a href="https://agentmods.dev/skills/ahmedhabiba/architor/architecture-patterns"><img src="https://agentmods.dev/badge/skills/ahmedhabiba/architor/architecture-patterns/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/ahmedhabiba/architor/architecture-patterns"><img src="https://agentmods.dev/badge/skills/ahmedhabiba/architor/architecture-patterns.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 | $0.00045 | $0.00661 |
| Opus 5 | $0.00023 | $0.00331 |
| Sonnet 5 | $0.00009 | $0.00132 |
| Haiku 4.5 | $0.00005 | $0.00066 |
Grade A, and why
architecture-patterns 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 9d 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.
Architecture Patterns Knowledge
Pattern Selection Framework
When recommending a pattern, evaluate against these criteria:
Team Fit
- Team size < 5 → Strongly favor monolith or modular monolith
- Team size 5-15 → Modular monolith or bounded microservices
- Team size 15+ → Microservices viable if org supports it
- No DevOps/Platform team → Avoid Kubernetes-heavy architectures
- Junior-heavy team → Favor simpler patterns with clear boundaries
Operational Reality
- 1 DevOps engineer → Cannot sustain >3 independently deployed services
- No dedicated DBA → Avoid polyglot persistence
- Limited monitoring experience → Start with monolith + good observability
- Budget constrained → Serverless for spiky loads, monolith for steady
Requirement Signals
- Independent scaling needs → Microservices or serverless
- Strong consistency requirements → Monolith or synchronous microservices
- Event-heavy domain → Event-driven architecture
- Read/write asymmetry → CQRS
- Rapid experimentation needed → Modular monolith (fastest to change)
- Regulatory isolation → Service per compliance boundary
Pattern Comparison Quick Reference
Monolith
- Best for: Small teams, rapid development, strong consistency needs
- Risks: Scaling bottleneck, deployment coupling, team scaling limits
- Migrate to: Modular monolith → microservices (progressive)
Modular Monolith
- Best for: Teams 3-10, need clear boundaries without operational overhead
- Risks: Module coupling creep, single deployment unit
- Migrate to: Extract modules to services as needed
Microservices
- Best for: Large teams, independent scaling, polyglot needs
- Risks: Distributed system complexity, data consistency, operational overhead
- Prerequisite: CI/CD maturity, monitoring, team autonomy
Event-Driven
- Best for: Async workflows, decoupled services, audit trails
- Risks: Eventual consistency complexity, debugging difficulty, event schema evolution
- Prerequisite: Team comfort with async patterns, good monitoring
What ships with it
19 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.
- evals/instructions.json 11 KB
- evals/scenario-0/capability.txt 29 B
- evals/scenario-0/criteria.json 2.0 KB
- evals/scenario-0/task.md 1.1 KB
- evals/scenario-1/capability.txt 42 B
- evals/scenario-1/criteria.json 2.1 KB
- evals/scenario-1/task.md 1.1 KB
- evals/scenario-2/capability.txt 35 B
- evals/scenario-2/criteria.json 2.5 KB
- evals/scenario-2/task.md 1.3 KB
- evals/scenario-3/capability.txt 18 B
- evals/scenario-3/criteria.json 1.4 KB
- evals/scenario-3/task.md 2.0 KB
- evals/scenario-4/capability.txt 46 B
- evals/scenario-4/criteria.json 2.4 KB
- evals/scenario-4/task.md 1.2 KB
- evals/summary_infeasible.json 58 B
- evals/summary.json 1022 B
- tile.json 410 B
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.
- 9d ago First seen · 72 lines · 45 tokens per session scan A 9c5cb5cbb6f6
architecture-patterns is a skill published in the GitHub repository AhmedHabiba/architor (6 stars, last pushed 6mo ago), licensed MIT. It adds 45 tokens to every session and 661 once invoked, about $0.0002 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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