• CRITICAL
  • DEBT
  • HUMAN
  • RISK

How to audit system architecture complexity with your AI

Connect Copernicus Perspective Prover to your AI client to find where your technical model is failing. It finds the specific points where workarounds have become the standard.

Ask AI about this page

Short answer

Is my system architecture actually broken?

Your AI finds structural rot by locating where special cases and manual workarounds are required to keep the system stable. You get a map of where your technical model fails its own logic. This includes a breakdown of specific failure points.

Where the issues land.

The audit outcomes.

The AI sorts its findings into these categories.

CRITICAL

Structural failures

The AI flags areas where the model is fundamentally broken. These are points where the logic cannot hold up without constant intervention.

DEBT

Accumulated workarounds

This identifies the specific special cases added over time. It shows how much glue is holding your architecture together.

HUMAN

Manual intervention

The AI highlights where a human must step in to fix or bypass a system error. These are the tasks your team shouldn't be doing.

RISK

Stability warnings

These are high-complexity areas where the logic is still valid but fragile. It marks where the next failure is likely to happen.

The workflow

What your AI does when the data arrives.

The AI processes your technical documentation and logs to find friction points.

  1. Map the logic

    The AI builds a model of how your components should interact based on your documentation.

    validate_copernicus_perspective

  2. Identify deviations

    It compares intended logic against actual behavior recorded in your system logs.

    validate_copernicus_perspective

  3. Count workarounds

    The agent looks for patterns of repetitive manual fixes or logic branches used for edge cases.

    validate_copernicus_perspective

  4. Generate audit

    The AI compiles these findings into a list of structural weaknesses and high-risk zones.

    validate_copernicus_perspective

Try it

Copy these to start.

Use these prompts to begin the audit.

Starting points

Replace the bracketed text with your specific file paths or repository names.

Copernicus Perspective Prover Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_jiRuMM7KNglBesR9KtIVKrRjuzelmGolCrKPXVQ9/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Copernicus Perspective Prover capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "copernicus-perspective-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jiRuMM7KNglBesR9KtIVKrRjuzelmGolCrKPXVQ9/mcp"
    }
  }
}
Copy into chat04

  • Audit the architecture in [repo_path] and find where we are using too many special cases.

  • Look at the error logs in [log_file] and tell me which parts of the system are being kept alive by workarounds.

  • Analyze [documentation_link] to see if the current technical model is fundamentally broken.

  • Identify the most complex areas in [system_diagram] where the logic is becoming unmanageable.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Copernicus Perspective Prover once, then ask.

Link the MCP to your client. Your credentials stay encrypted, and you can start auditing immediately.

Connect Copernicus Perspective Prover to your AI

FAQ

How this task behaves.

  • 01

    Can the AI fix my architecture?

    No. The AI identifies the flaws and counts the workarounds, but you have to design and implement the fixes.

  • 02

    Does the AI change my code?

    No. This MCP only reads your data to perform the audit. It cannot write to your files or change your system settings.

  • 03

    What data does it need?

    It needs access to your technical documentation, system logs, or code repositories to identify complexity patterns.

  • 04

    Can it suggest specific code changes?

    No. It identifies where the logic is broken, but it does not generate or suggest new code implementations.

  • 05

    How does it detect a workaround?

    It looks for repetitive patterns of manual intervention or logic branches that exist only to bypass standard system flows.

  • More questions about Copernicus Perspective Prover? The Connector page answers them. See everything the Copernicus Perspective Prover Connector can do

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