Does this skill require an external database?

Yes, it utilizes a Qdrant collection (local or remote) to store and query high-dimensional vector embeddings of the ingested documentation.

How does it improve AI-generated Rust code?

It provides the AI agent with real-time access to canonical documentation and patterns, ensuring the output is idiomatic and follows current best practices rather than potentially outdated training data.

What sources can Rust Librarian ingest?

It supports official books like The Rust Book and Rustonomicon, the standard library API, design patterns, guidelines, and crate documentation from docs.rs.

Can I use this to fix specific Rust compiler errors?

Yes, the skill can search the official Rust error index for specific codes (e.g., E0502) to find clear explanations and recommended fix patterns.

What embedding model does it use?

It uses the sentence-transformers all-mpnet-base-v2 model, which produces 768-dimensional embeddings for high-quality semantic retrieval.

Rust Librarian

Name: Rust Librarian
Author: lev-os

bylev-os

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Aprendizaje y Documentación

Indexes and retrieves authoritative Rust knowledge, design patterns, and compiler error solutions via semantic search in Qdrant.

Rust Librarian is a specialized RAG (Retrieval-Augmented Generation) system designed to provide Claude with direct access to canonical Rust documentation and idiomatic patterns. By indexing high-quality sources like The Rust Book, the Rustonomicon, and the official error index into a Qdrant vector database, it ensures that AI-generated code adheres to current best practices rather than relying solely on static training data. This skill is indispensable for developers needing accurate architectural guidance, idiomatic solutions to complex borrow checker errors, and deep-dives into popular crate documentation during the planning and implementation phases of the software development lifecycle.

Características Principales

01Structured chunking strategies tailored to books, API docs, and design patterns for maximum relevance.

021 GitHub stars

03Specialized indexing of Rust compiler errors (E0xxx) with associated fixes and explanations.

04Multi-source ingestion from official Rust books, API guidelines, and community patterns.

05Semantic search using sentence-transformers (all-mpnet-base-v2) for context-aware retrieval.

06Integration-ready search commands for enriching agent planning and compile-fix loops.

Casos de Uso

01Retrieving idiomatic design patterns and lifetime elision rules during the architectural planning phase.

02Onboarding agents to new crates by ingesting and searching specific documentation directly from docs.rs.

03Troubleshooting specific Rust compiler errors by searching for canonical explanations and fix examples.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lev-os/agents rust-librarian

For use in Claude.ai and ChatGPT