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code-intelligence | superpowers

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superpowers
code-intelligence

Skill

code-intelligence

From superpowers

Use when working on large, multi-service codebases where semantic search and global project context are needed to find relevant code or explain architecture.

Invocation

How this skill is triggered — by the user, by Claude, or both

Slash command

/superpowers:code-intelligence

User invocable

Model invocable

Inline context

Default effort

Context Preview

The summary Claude sees in its skill listing — used to decide when to auto-load this skill

A semantic search and retrieval system powered by LanceDB and KConsole Gemini Embeddings. It allows you to search your codebase by "meaning" rather than just keywords.

Supporting Files

scripts/indexer.py

SKILL.md

37 lines · ~350 tokens

Stats

LanguageShell

Stars0

MaintenanceExcellent

Last CommitApr 17, 2026

Actions

View Source View Plugin View on GitHub View README

Stats

LanguageShell

Stars0

MaintenanceExcellent

Last CommitApr 17, 2026

Actions

View Source View Plugin View on GitHub View README

Code Intelligence (LanceDB)

Overview

A semantic search and retrieval system powered by LanceDB and KConsole Gemini Embeddings. It allows you to search your codebase by "meaning" rather than just keywords.

When to Use

You need to find code but don't know the exact filenames or variable names.
Working across multiple microservices where dependencies are unclear.
"Remembering" architecture patterns from different parts of the project.

Usage

1. Index your Project

Run this in a background tmux pane to build the initial memory: ```bash python scripts/indexer.py --index ./your-project ```

2. Semantic Search

Ask for a concept, not a keyword: ```bash python scripts/indexer.py --search "How is the user authentication handled?" ```

Best Practices

Exclude noise: The indexer automatically ignores hidden files and common build artifacts.
Refresh: Re-index after major refactors or adding new services.
Combined with tmux: Keep a "Monitor" pane open to run the indexer in the background.

Implementation

The system uses `text-embedding-004` via KConsole AI Gateway and stores vectors in a local LanceDB instance (`.lancedb`).

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npx claudepluginhub hangsiahong/superpowers-koompi --plugin superpowers