Sub-skill of rag-system-builder: 1. Cache Embeddings (+2).
Scanned 9/9/2026
Install to Claude Code
npx -y skills add vamseeachanta/workspace-hub --skill 1-cache-embeddings --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: rag-system-builder-1-cache-embeddings
description: 'Sub-skill of rag-system-builder: 1. Cache Embeddings (+2).'
version: 1.2.0
category: data
type: reference
scripts_exempt: true
---
# 1. Cache Embeddings (+2)
## 1. Cache Embeddings
```python
# Load all embeddings into memory at startup
self.embedding_cache = self._load_all_embeddings()
```
## 2. Use FAISS for Large Collections
```python
import faiss
# Build FAISS index for fast similarity search
index = faiss.IndexFlatIP(dimension) # Inner product for cosine sim
index.add(embeddings)
```
## 3. Batch Queries
```python
# Process multiple questions efficiently
questions = ["Q1", "Q2", "Q3"]
query_embeddings = model.embed_batch(questions)
```
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Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.