tos-vectors
⚠Review·Scanned 2/18/2026
This skill manages vector storage and similarity search using the TOS Vectors service and includes code and scripts to create buckets, indexes, insert and query vectors. It reads TOS_ACCESS_KEY, TOS_SECRET_KEY, and TOS_ACCOUNT_ID, calls https://tosvectors-cn-beijing.volces.com, and instructs running python scripts/init_vectors.py.
from clawhub.ai·va49fa74·37.9 KB·0 installs
Scanned from 1.0.2 at a49fa74 · Transparency log ↗
$ vett add clawhub.ai/jneless/tos-vectorsReview findings below
TOS Vectors Agent Skill
A comprehensive Claude Agent Skill for managing vector storage and similarity search using TOS Vectors service.
Overview
This skill enables Claude to work with TOS Vectors - a cloud-based vector database optimized for AI applications including semantic search, RAG systems, and recommendation engines.
Skill Structure
tos-vectors-skill/
├── SKILL.md # Main skill file with quick start and core operations
├── REFERENCE.md # Complete API reference
├── WORKFLOWS.md # Common workflow patterns
├── scripts/ # Utility scripts
│ ├── init_vectors.py # Initialize bucket and index
│ ├── insert_vectors.py # Insert sample vectors
│ └── search_vectors.py # Search vectors
└── examples/ # Additional examples
Quick Start
1. Set Environment Variables
export TOS_ACCESS_KEY="your-access-key"
export TOS_SECRET_KEY="your-secret-key"
export TOS_ACCOUNT_ID="your-account-id"
2. Initialize Environment
python scripts/init_vectors.py
3. Insert Sample Data
python scripts/insert_vectors.py
4. Search Vectors
python scripts/search_vectors.py "machine learning"
Core Capabilities
- Vector Bucket Management: Create, list, delete vector buckets
- Vector Index Management: Create indexes with custom dimensions and metrics
- Vector Operations: Insert, query, get, delete, and list vectors
- Similarity Search: KNN search with metadata filtering
- Batch Operations: Efficient batch insert/delete (up to 500/100 vectors)
- Policy Management: IAM policy configuration
Common Use Cases
- Semantic Search: Build document search systems
- RAG Systems: Retrieval augmented generation for LLMs
- Recommendations: Product/content recommendation engines
- Image Search: Visual similarity search
Documentation
- SKILL.md: Quick reference and common operations
- REFERENCE.md: Complete API documentation
- WORKFLOWS.md: Step-by-step workflow examples
Requirements
- Python 3.7+
tosPython SDK- TOS Vectors account credentials
Installation
pip install tos
- important: TOS vectors in Beta, please install tos=2.8.8b1
Configuration
Endpoints
- Internal:
https://tosvectors-cn-beijing.ivolces.com - External:
https://tosvectors-cn-beijing.volces.com
Regions
cn-beijing(Beijing)cn-shanghai(Shanghai)cn-guangzhou(Guangzhou)
Limits
- Max vector buckets: 100 per account
- Vector dimensions: 1-4096
- Batch insert: 1-500 vectors
- Batch get/delete: 1-100 vectors
- Query TopK: 1-30 results
Support
For issues or questions, refer to the TOS Vectors documentation or contact support.