tomevault-io LangChain Skills
Use this skill when the task involves LangChain application architecture, provider integrations, or WhatsApp-based agent flows.
Focus
- Match the task to the right LangChain building blocks before writing code
- Reuse the codebase's existing LLM, embedding, retriever, and tool abstractions
- Prefer concrete chains, tools, and state flow over vague agent scaffolding
- Check provider-specific integration docs before choosing packages or APIs
Working Approach
- Inspect the repository for current LangChain packages, providers, and agent patterns.
- Determine whether the task is about retrieval, tool use, messaging, or orchestration.
- Check the official integration docs before proposing package imports or usage.
- Implement the narrowest change that fits the current architecture.
- Mention any follow-up validation for prompts, tracing, or external provider credentials.
References
- LangChain WhatsApp provider integrations: https://docs.langchain.com/oss/python/integrations/providers/whatsapp
- Example repo to consider: https://github.com/worldbank/WhatsApp-RAG-Example
Source: ruslands/plugins — distributed by TomeVault.