swain-knowledge

Query and store boat knowledge in a local vector database via the swain CLI.

1|Updated Feb 9, 2026

Search Tags:#embeddings #workspace #knowledge #vector #semantic-search #swain #boat

Ready to run

npx skills add https://github.com/peteknowsai/swain-agents --skill swain-knowledge

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: swain-knowledge
Source: https://github.com/peteknowsai/swain-agents/tree/main/skills/swain-knowledge
Command: npx skills add https://github.com/peteknowsai/swain-agents --skill swain-knowledge

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables fast access to a local knowledge base stored as vector embeddings, allowing semantically relevant context during planning and decision-making for boat operations.

Core Features & Use Cases

Knowledge storage: persist observations, sensor readings, maintenance notes, and captain conversations to a local vector database.
Semantic retrieval: retrieve contextually relevant entries to inform scans, heartbeats, and captain briefings.
Use Case: before a hull inspection, query past notes to surface recurring issues and recommended actions.

Quick Start

Query my local knowledge base for hull condition and add the latest inspection notes.

Frequently Asked Questions about swain-knowledge

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

FAQPage Schema

How do I store boat maintenance notes in a local vector database for later retrieval?▼

You can store boat maintenance notes in a local vector database by saving observations and sensor readings as vector embeddings. This allows semantic retrieval of past entries to inform planning and decision-making for boat operations.

What is semantic search for boat knowledge and how does it help with hull inspections?▼

Semantic search for boat knowledge retrieves contextually relevant entries from a local vector database using meaning rather than exact keywords. Before a hull inspection, it surfaces recurring issues and recommended actions from past notes to support smarter decisions.

Can I use a local vector database to query past captain conversations and sensor readings?▼

Yes, you can persist captain conversations and sensor readings to a local vector database. It uses semantic search to retrieve relevant entries, providing contextually accurate information during heartbeats, scans, and captain briefings.

How do I retrieve relevant boat observations using semantic search before generating scan scripts?▼

You retrieve relevant boat observations by querying the local vector database via the swain CLI before generating scan scripts. It uses semantic search to match your query with stored vector embeddings, returning contextually relevant entries.

Do I need the swain CLI to query and store local boat knowledge?▼

Yes, the swain CLI is required to interact with the local vector database for storing and retrieving boat knowledge. It integrates with the database to perform semantic search and retrieve relevant entries.

What are the limitations of using a local vector database for boat knowledge storage?▼

A local vector database for boat knowledge storage is limited to the local environment, meaning data is not automatically synced across multiple devices or remotely accessible without additional network configuration.