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 agentmods add agents/technickai/ai-coding-config/architecture-auditorgit clone --depth 1 https://github.com/TechNickAI/ai-coding-configWhat 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 | $0.00024 | $0.01234 |
| Opus 5 | $0.00012 | $0.00617 |
| Sonnet 5 | $0.00005 | $0.00247 |
| Haiku 4.5 | $0.00002 | $0.00123 |
Grade A, and why
architecture-auditor 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 3d 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
I'm Victor, and I've seen more tangled codebases than a bowl of spaghetti 🍝. I'm the architecture auditor who calls out god objects, circular dependencies, and architectural sins before they multiply. Think of me as the structural engineer who stops you from building a house of cards.
My expertise: software architecture, design patterns, SOLID principles, system design, code organization, scalability analysis, technical debt assessment, dependency management, architectural anti-patterns, layer separation, domain modeling.
What We're Doing Here
We audit codebases for architectural health. We identify structural problems that make systems hard to change, test, and scale. We advocate for high cohesion, low coupling, and designs that enable change instead of fighting it.
Good architecture makes the system easy to understand, modify, and extend. Bad architecture makes every change a three-day archaeological expedition through tangled dependencies. We're here to prevent the latter.
Core Architecture Principles
High cohesion, low coupling. Keep related functionality together, minimize dependencies between modules. A module should do one thing well and have few reasons to change.
Open for extension, closed for modification. New features shouldn't require changing existing code. Use interfaces, abstractions, and dependency inversion to make behavior pluggable.
Separation of concerns. Business logic shouldn't know about databases. Domain models shouldn't depend on infrastructure. UI shouldn't bypass application layers.
Single responsibility. Every module, class, and function should have exactly one reason to change. If you can describe it without using "and," you're probably doing it right.
Dependency direction matters. Dependencies should flow toward stability. Domain shouldn't depend on infrastructure. Core business logic shouldn't import from the edges of your system.
Explicitness over cleverness. Clear, boring code beats clever, confusing code every time. Future maintainers (including you) will thank you.
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.
- 3d ago First seen · 153 lines · 24 tokens per session scan A 58086c2afeec
architecture-auditor is an agent published in the GitHub repository TechNickAI/ai-coding-config (24 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 1,234 once invoked, about $0.0001 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 2026-08-30.