148 lines
3.5 KiB
Markdown
148 lines
3.5 KiB
Markdown
---
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name: rag-retrieve
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description: RAG retrieval skill for querying and retrieving relevant documents from knowledge base. Use this skill when users need to search documentation, retrieve knowledge base articles, or get context from a vector database. Supports semantic search with configurable top-k results.
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---
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# RAG Retrieve
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## Skill Structure
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This is a **self-contained skill package** that can be distributed independently. The skill includes its own scripts and configuration:
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```
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rag-retrieve/
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├── SKILL.md # Core instruction file (this file)
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├── skill.yaml # Skill metadata
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├── scripts/ # Executable scripts
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│ └── rag_retrieve.py # Main RAG retrieval script
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```
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## Overview
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Query and retrieve relevant documents from a RAG (Retrieval-Augmented Generation) knowledge base using vector search. This skill provides semantic search capabilities with support for multiple bot instances and configurable result limits.
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## Required Parameters
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Before executing any retrieval, you MUST confirm the following required parameters with the user if they are not explicitly provided:
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| Parameter | Description | Type |
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|-----------|-------------|------|
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| **query** | Search query content | string |
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### Optional Parameters
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| Parameter | Description | Type | Default |
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|-----------|-------------|------|---------|
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| **top_k** | Maximum number of results | integer | 100 |
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### Confirmation Template
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When the required parameter is missing, ask the user:
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```
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I need some information to perform the RAG retrieval:
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1. Query: What would you like to search for?
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```
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## Quick Start
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Use the `scripts/rag_retrieve.py` script to execute RAG queries:
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```bash
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scripts/rag_retrieve.py --query "your search query"
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```
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## Usage Examples
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### Basic Query
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```bash
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scripts/rag_retrieve.py --query "How to configure authentication?"
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```
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### Search with Specific Top-K
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```bash
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scripts/rag_retrieve.py --query "API error handling" --top-k 50
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```
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### Common Use Cases
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**Scenario 1: Documentation Search**
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```bash
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scripts/rag_retrieve.py --query "deployment guide"
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```
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**Scenario 2: Troubleshooting**
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```bash
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scripts/rag_retrieve.py --query "connection timeout error"
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```
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**Scenario 3: Feature Information**
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```bash
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scripts/rag_retrieve.py --query "enterprise pricing plans"
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```
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## Script Usage
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### rag_retrieve.py
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Main script for executing RAG retrieval queries.
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```bash
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scripts/rag_retrieve.py [OPTIONS]
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```
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**Options:**
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| Option | Required | Description | Default |
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|--------|----------|-------------|---------|
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| `--query`, `-q` | Yes | Search query content | - |
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| `--top-k`, `-k` | No | Maximum number of results | 100 |
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**Examples:**
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```bash
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# Basic query
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scripts/rag_retrieve.py --query "authentication setup"
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# Custom top-k
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scripts/rag_retrieve.py --query "API reference" --top-k 20
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```
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## Common Workflows
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### Research Mode: Comprehensive Search
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```bash
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scripts/rag_retrieve.py --query "machine learning algorithms" --top-k 100
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```
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### Quick Answer Mode: Focused Search
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```bash
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scripts/rag_retrieve.py --query "password reset" --top-k 10
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```
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### Comparison Mode: Multiple Queries
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```bash
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# Search for related topics
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scripts/rag_retrieve.py --query "REST API" --top-k 30
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scripts/rag_retrieve.py --query "GraphQL API" --top-k 30
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```
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## Resources
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### scripts/rag_retrieve.py
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Executable Python script for RAG retrieval. Handles:
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- HTTP requests to RAG API
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- Authentication token generation
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- Configuration file loading
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- Error handling and reporting
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- Markdown response parsing
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The script can be executed directly without loading into context.
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