mcp-zen-of-languages: Instructions file for GitHub Copilot

.github/instructions/architecture.instructions.md

mcp-zen-of-languages architecture.instructions.md is an instructions file for GitHub Copilot from Anselmoo/mcp-zen-of-languages. It costs 2,472 tokens per session, scanned A, original, MIT.

A guide for restructuring a code analyzer so its parsing, measurements, problem detection, and output are separate parts. It describes reusable patterns for supporting multiple programming languages.

In plain words
What is it for?
It is for planning or implementing a cleaner analyzer architecture with language-specific parts and independently testable detectors.
Why use it?
It addresses large, tangled analyzer code that is difficult to extend and test.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file.

This is Anselmoo/mcp-zen-of-languages's own configuration. It tells GitHub Copilot how to work on mcp-zen-of-languages itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything mcp-zen-of-languages configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/Anselmoo/mcp-zen-of-languages/main/.github/instructions/architecture.instructions.md
Clone the repo
git clone --depth 1 https://github.com/Anselmoo/mcp-zen-of-languages

Made for: GitHub Copilot.

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Origin original No closer match found in the catalogue.
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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.

.github/instructions/architecture.instructions.md · 382 lines

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:

  1. 400+ lines in a single method
  2. Deeply nested (5+ levels)
  3. Mixed concerns (parsing, metrics, detection, formatting)
  4. Dictionary-based config instead of Pydantic
  5. Hard to extend to other languages
  6. Hard to test individual detectors
  7. 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
        ...

Read the full file on GitHub · 382 lines

Changes

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.

  1. 11d ago First seen · 382 lines · 2,472 tokens per session scan A 78b482b9d617

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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.

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