AI Workspace Glossary
Key terminology for understanding AI workspace hygiene. Naqi helps you recognize and eliminate each of these issues.
Memory Rot
Memories saved by Claude or other AI tools about projects, concepts, or decisions that are no longer relevant, but remain active in your workspace and continue to influence responses.
Example:
A memory from a project you shipped 6 months ago that Claude brings up in every conversation, even when irrelevant.
How Naqi helps:
Naqi detects and flags potentially stale memories based on age and relevance patterns. You can review and archive them before they confuse your AI.
Config Sprawl
The accumulation of MCP servers, skills, and tool integrations across your AI clients over time, where many are no longer used or maintained.
Example:
You installed 15 MCP servers for different projects, but only actively use 5. The other 10 are still connected, adding noise and consuming context.
How Naqi helps:
Naqi scans all 10 AI clients in seconds and shows you exactly which servers are stale, broken, or duplicated. Cleanup is one click away.
Ghost Server
An MCP server or tool integration that is configured but no longer functional, reachable, or actively maintained — it fails every time the AI tries to use it.
Example:
A GitHub MCP server that was set up for a closed repository; it's still in your config but returns "404 not found" every time Claude tries to access it.
How Naqi helps:
Naqi's health check pings every server and marks broken ones as "Ghost Servers." Remove them in bulk to reduce errors and latency.
Context Bloat
The waste of precious token context caused by unused, duplicate, or stale configuration — every request to your AI is forced to process irrelevant config that consumes context window space.
Example:
Your workspace has 50 MCP servers but you only use 5. On every request, Claude's context is filled with metadata about 45 servers you don't need, leaving less room for your actual task.
How Naqi helps:
Naqi quantifies context savings: cleaning up your workspace can free 10-20% of your context window for actual work.
Skill Creep
The accumulation of installed skills, plugins, or extensions in your AI clients over time — many are never used or become obsolete as your workflow changes.
Example:
You installed 8 skills from tutorials and GitHub repos, but only actively use 2. The other 6 are loaded on startup but never triggered.
How Naqi helps:
Naqi lists all installed skills grouped by client, shows when each was last modified, and highlights unused ones for cleanup.
Cross-Client Drift
Inconsistencies and duplicates in configuration across different AI clients — the same MCP server configured differently in Claude Desktop vs Cursor vs VS Code, or the same memory saved twice with slightly different content.
Example:
You set up the GitHub MCP server in Claude Desktop with one auth token, but in Cursor with a different token. Or you saved the same project context as two separate memories that contradict each other.
How Naqi helps:
Naqi detects config drift across clients and memory contradictions. It shows you exactly where inconsistencies exist so you can align them.
See these issues in your workspace?
Download Naqi and scan in 3 seconds. Identify memory rot, config sprawl, ghost servers, and more.
Download for macOS