KS
Killer-Skills

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v1.0.0
GitHub

About this Skill

Ideal for Code Analysis Agents requiring comprehensive tech stack review and file categorization capabilities. 3-identifying-architecture is a code analysis skill that reviews tech stacks and categorized files to understand codebase structure and major concerns.

Features

Reviews tech stacks summarized in ./{output-folder}/1-techstack.md
Analyzes categorized files listed in ./{output-folder}/2-file-categorization.json
Permits thorough review of codebase without time constraints
Ensures accuracy and completeness of results
Supports detailed analysis of codebase structure and major concerns

# Core Topics

bitovi bitovi
[0]
[0]
Updated: 1/2/2026

Quality Score

Top 5%
39
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add bitovi/context-generation-mvp/3-identifying-architecture

Agent Capability Analysis

The 3-identifying-architecture MCP Server by bitovi is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use 3-identifying-architecture, what is 3-identifying-architecture, 3-identifying-architecture alternative.

Ideal Agent Persona

Ideal for Code Analysis Agents requiring comprehensive tech stack review and file categorization capabilities.

Core Value

Empowers agents to thoroughly review codebases by analyzing tech stacks summarized in .md files and categorized files listed in .json formats, ensuring accurate and complete results through meticulous review of files without skipping or producing partial results.

Capabilities Granted for 3-identifying-architecture MCP Server

Analyzing code structure for major concerns
Reviewing tech stacks for optimization opportunities
Categorizing files for efficient project organization

! Prerequisites & Limits

  • Requires access to codebase files
  • May require significant time for complex codebases
  • Needs output folder with 1-techstack.md and 2-file-categorization.json for accurate analysis
Project
SKILL.md
3.1 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

[No tags]
SKILL.md
Readonly

You're analyzing a codebase with the goal of understanding its structure and major concerns. The tech stack is summarized in ./{output-folder}/1-techstack.md. Categorized files are listed in ./{output-folder}/2-file-categorization.json.

This task may take some time — that is expected and acceptable. Do not skip files or produce partial results due to time or complexity. Accuracy and completeness are mission-critical. You are permitted to take as long as necessary to:

  • Review every relevant file
  • Extract actual patterns and conventions
  • Produce complete, high-fidelity output If a file is listed in ./{output-folder}/2-file-categorization.json or is part of a relevant domain, it must be included in your analysis. Do not optimize for speed or brevity. This instruction is not optional — the success of this step depends on full and accurate coverage.

Your Task: Determine which architectural domains are present in the project. Consider:

  • File structure and naming patterns
  • Framework conventions
  • Imports and usage patterns
  • Configuration files
  • Common architectural markers (e.g., components/, routes/, handlers/, services/, cli/, etc.)

Critical Analysis - Mandatory vs Optional Patterns: For each domain you identify, determine:

  • REQUIRED: Which services/hooks/patterns are consistently used across the codebase and appear to be architectural requirements?
  • CONSTRAINTS: What types of implementations are clearly expected? (e.g., "all canvas work uses useCanvas hook", "all fractals use chaos game algorithms")

Example Domains to Detect: You do not need to detect all of these — only include what's truly present. There may also be domains that aren't listed here but are relevant to this specific project. Include any meaningful domains you identify.

Examples:

  • ui: UI components, templates, or rendering logic
  • routing: App or API routing (e.g., Next.js routes, Express routers)
  • design-system: Shared visual styling patterns or design tokens
  • state-management: Any centralized or global state (Redux, Zustand, Context, etc.)
  • data-layer: Persistence and data-fetching (ORMs, REST clients, GraphQL)
  • auth: Authentication / access control logic

Output: Write a JSON object to ./{output-folder}/3-architectural-domains.json like so:

json
1{ 2 "ui": { 3 "required_patterns": { 4 "canvas-rendering": "use useCanvas", 5 "mathematical-computing": "..." 6 }, 7 "architectural_constraints": { 8 "canvas-rendering": "...", 9 "mathematical-computing": "..." 10 } 11 } 12}

Only include domains you find concrete evidence for based on the actual codebase.

This analysis will help ensure future additions follow the established architectural patterns rather than introducing inconsistent approaches.

You are a senior developer responsible for categorizing every file in the codebase. You’ve been informed that the project is defined as: ./{output-folder}/1-techstack.md (read this file first)

After writing ./{output-folder}/3-file-categorization.json, continue to skill 4-domain-deep-dive and proceed accordingly with {output-folder} as the output-folder.

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