Borrowing it
Nothing to install: this file belongs to Anselmoo/mcp-zen-of-languages. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Anselmoo/mcp-zen-of-languages/main/.github/instructions/architecture.instructions.mdgit clone --depth 1 https://github.com/Anselmoo/mcp-zen-of-languagesWrote 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/instructions/anselmoo/mcp-zen-of-languages/architecture)<a href="https://agentmods.dev/instructions/anselmoo/mcp-zen-of-languages/architecture"><img src="https://agentmods.dev/badge/instructions/anselmoo/mcp-zen-of-languages/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/instructions/anselmoo/mcp-zen-of-languages/architecture"><img src="https://agentmods.dev/badge/instructions/anselmoo/mcp-zen-of-languages/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 | $0.02472 | $0.02472 |
| Opus 5 | $0.01236 | $0.01236 |
| Sonnet 5 | $0.00494 | $0.00494 |
| Haiku 4.5 | $0.00247 | $0.00247 |
Grade A, and why
mcp-zen-of-languages architecture.instructions.md 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 11d 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 — 382 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzer Architecture Refactoring
Problem Statement
The original PythonAnalyzer.analyze() method had multiple anti-patterns:
- ❌ 400+ lines in a single method
- ❌ Deeply nested (5+ levels)
- ❌ Mixed concerns (parsing, metrics, detection, formatting)
- ❌ Dictionary-based config instead of Pydantic
- ❌ Hard to extend to other languages
- ❌ Hard to test individual detectors
- ❌ No separation of concerns
Solution: Architectural Patterns
We use a combination of proven design patterns:
1. Template Method Pattern (Base Structure)
Purpose: Define the analysis algorithm skeleton in the base class, with hooks for language-specific behavior.
class BaseAnalyzer(ABC):
def analyze(self, code: str, ...) -> AnalysisResult:
# Template method - defines the flow
context = self._create_context(...)
context.ast_tree = self.parse_code(code) # Hook
metrics = self.compute_metrics(...) # Hook
violations = self.pipeline.run(context, config)
return self._build_result(context, violations)
@abstractmethod
def parse_code(self, code: str) -> ParserResult:
pass # Language-specific hook
@abstractmethod
def compute_metrics(self, ...) -> tuple:
pass # Language-specific hook
Benefits:
- ✅ Common flow defined once
- ✅ Language-specific parts isolated
- ✅ Easy to maintain the overall structure
2. Strategy Pattern (Detectors)
Purpose: Encapsulate each violation detection algorithm in its own class.
class ViolationDetector(ABC):
@abstractmethod
def detect(self, context: AnalysisContext, config: AnalyzerConfig) -> list[Violation]:
pass
class CyclomaticComplexityDetector(ViolationDetector):
def detect(self, context, config) -> list[Violation]:
# Focused, single-responsibility logic
...
class NestingDepthDetector(ViolationDetector):
def detect(self, context, config) -> list[Violation]:
# Each detector is independent
...
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.
- 11d ago First seen · 382 lines · 2,472 tokens per session scan A 78b482b9d617
mcp-zen-of-languages architecture.instructions.md is an instructions file published in the GitHub repository Anselmoo/mcp-zen-of-languages (2 stars, last pushed 2d ago), licensed MIT. It adds 2,472 tokens to every session, about $0.0124 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.
Other instructions, from other repositories
klaussy-agents fastapi.instructions.md
Instructions for steph-dove/klaussy-agents: Example context from fastapi/applications.py (lines 214-220).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.