Semantic Code Search

Name: Semantic Code Search
Availability: InStock
Author: LightOn

Locate source code by semantic intent with regex and file filters.

527|61|Updated Jan 6, 2026

Search Tags:#semantic search #code search #codebase navigation #developer tooling #regex filtering #colgrep

Ready to run

npx skills add https://github.com/lightonai/next-plaid --skill semantic-code-search-lightonai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Semantic Code Search
Source: https://github.com/lightonai/next-plaid/tree/main/skills/colgrep
Command: npx skills add https://github.com/lightonai/next-plaid --skill semantic-code-search-lightonai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you locate relevant code faster when exact file names, symbols, or paths are unknown, reducing time spent on broad grep-style searching.

Core Features & Use Cases

Semantic Retrieval: Search by intent or natural language to find functions, classes, and implementations that match a concept.
Hybrid Filtering: Combine semantic queries with text or regex filters to narrow results precisely.
Targeted Code Exploration: Search specific files, folders, or file types while retrieving ranked matches for debugging, refactoring, or codebase discovery.
Use Case: Ask for code related to connection pooling, authentication flows, or async error handling, and surface the most relevant Rust, Python, or TypeScript locations.

Quick Start

Use colgrep to search the repository for the code that most closely matches your intent, then refine the result set with file filters or regex when needed.

Frequently Asked Questions about Semantic Code Search

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

FAQPage Schema

How do I find code by intent instead of exact filenames or literal text matches?▼

Semantic code search locates relevant source code by matching natural language intent rather than exact strings. It uses semantic ranking and hybrid regex filters to retrieve ranked matches for codebase exploration, debugging, and refactoring.

What is the best way to search for a specific implementation concept like connection pooling across a large codebase?▼

The best way to find implementations like connection pooling is using semantic codebase navigation. This approach applies semantic retrieval to surface functions and classes matching your conceptual query, then refines results using file scoping and regex prefilters.

Can I narrow semantic search results to specific files, folders, or language patterns?▼

Yes, semantic code search supports targeted code exploration through hybrid filtering. You can combine natural language queries with regex prefilters, file scoping, and ranked result controls to search specific files, folders, or language patterns precisely.

Does semantic code search work with different programming languages like Rust, Python, or TypeScript?▼

Semantic code search works across Rust, Python, and TypeScript codebases. It applies semantic ranking to retrieve relevant code locations regardless of the specific programming language, helping developers discover implementations for async error handling or authentication flows.

When should I use semantic code search instead of broad grep-style searching?▼

Use semantic code search instead of broad grep-style searching when exact file names, symbols, or paths are unknown. It excels at codebase discovery by matching conceptual intent and natural language queries, reducing time spent on manual literal text searches.