3-identifying-architecture

Third step in building instruction context for codebase

181 stars

Best use case

3-identifying-architecture is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Third step in building instruction context for codebase

Teams using 3-identifying-architecture should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/3-identifying-architecture/SKILL.md --create-dirs "https://raw.githubusercontent.com/majiayu000/claude-skill-registry/main/skills/data/3-identifying-architecture/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/3-identifying-architecture/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How 3-identifying-architecture Compares

Feature / Agent3-identifying-architectureStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Third step in building instruction context for codebase

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

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
{
  "ui": {
    "required_patterns": {
      "canvas-rendering": "use useCanvas",
      "mathematical-computing": "..."
    },
    "architectural_constraints": {
      "canvas-rendering": "...",
      "mathematical-computing": "..."
    }
  }
}
```

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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