skills.rest
mahmoudimus
mahmoudimusCOMMUNITY
Explore all skills by this author →
Website𝕏@mahmoudimusGitHub

turbo-index

Index a project's codebase with QMD for semantic search.

6|1|Updated Feb 6, 2026
Search Tags:#indexing#codebase#optimization#search#qmd#simba
One-click install
npx skills add https://github.com/mahmoudimus/simba --skill turbo-index-mahmoudimus
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: turbo-index
Source: https://github.com/mahmoudimus/simba/tree/main/skills/turbo-index
Command: npx skills add https://github.com/mahmoudimus/simba --skill turbo-index-mahmoudimus

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires qmd, simba, and includes scripts (resource) components.

What problem does it solve?

This Skill addresses the challenge of inefficient code exploration and token waste by creating an optimized, searchable index of a project's codebase.

Core Features & Use Cases

  • Semantic Search Indexing: Indexes Markdown files using QMD for fast, semantic retrieval.
  • Dependency Management: Checks and installs necessary Python dependencies for QMD and Simba.
  • Project Memory Initialization: Sets up a local SQLite database for project-specific memory.
  • Codebase Mapping: Optionally runs a 'cartographer' tool to map codebase structure.
  • Use Case: When starting on a new project or after significant code changes, run this skill to ensure that subsequent AI interactions are highly efficient, reducing the need to re-read or re-explain project context.

Quick Start

Run the turbo-index skill to index the current project for optimized search.

Frequently Asked Questions about turbo-index

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize semantic search for a codebase to reduce AI token waste?▼

To optimize semantic search and reduce token waste, run this skill to index your codebase using QMD for vector embedding creation and fast file suggestions. It initializes a local SQLite database for project memory.

What dependencies do I need to run QMD for codebase indexing?▼

You need Python 3.12+, uv for dependency management, and QMD installed and configured to run codebase indexing. The skill also checks and installs necessary Python dependencies for Simba.

Does codebase indexing with QMD support mapping project structure?▼

Yes, codebase indexing with QMD optionally runs a cartographer tool to map project structure. It also sets up project memory initialization using a local SQLite database for optimized semantic retrieval.

When should I re-index a project for optimized semantic search?▼

You should re-index a project for optimized semantic search when starting a new project or after significant code changes. This ensures subsequent AI interactions remain highly efficient without re-reading project context.

What is the best way to set up project memory for AI-assisted code exploration?▼

The best way to set up project memory for AI-assisted code exploration is initializing a local SQLite database using QMD. This stores vector embeddings and project-specific memory to prevent token waste during onboarding.

Related Skills

Explore More Software Engineering Skills→
truongnattruongnat

python-pro

Develop Python 3.12+ applications with typing, Poetry/UV, and Pytest.

Community
Advanced
akselikorhonen-siiliakselikorhonen-siili

semantic-search

Perform vector-based semantic search over indexed document collections.

Community
Intermediate
davekilleendavekilleen
461

enable-semantic-search

Install and configure qmd for local semantic search in a vault.

Community
Advanced
jonathan-vellajonathan-vella
50

context-optimizer

Audit agent context window usage by parsing debug logs and profiling token consumption.

Community
Intermediate