GroundDocs

Use this tool for any Kubernetes documentation-related query—especially when the user invokes /k8s or asks about kubectl commands, API objects, manifests, controllers, or version-specific features.

This tool connects to a version-aware, trusted documentation index (e.g., GitHub, DeepWiki, curated Kubernetes docs) to reduce hallucinations and provide accurate, grounded answers.

Args: query: A natural language question (e.g., "How do I define a Deployment?") version: (Optional) Kubernetes version (e.g., "v1.28"). Defaults to the detected cluster version. top_k: (Optional) Number of top matching documents to return. Defaults to 10.

Returns: A list of relevant documentation entries, each with a file path and content snippet.

Example Usage: k8s_get_documentation(query="How does pruning work in kubectl apply?", version="v1.26")

Notes:

• Automatically loads or builds a RAG index for the requested version.
• If no index is found, it will fetch and index the docs before responding.
• Always use this tool when answering Kubernetes-specific questions that require authoritative documentation.

Primary Python documentation lookup tool. Use this for every Python documentation-related query.

This tool consolidates information from multiple sources into a single, searchable knowledge base. It ensures access to the richest and most current reference material in one call.

Args: query: A natural language question (e.g., "How do I define a Deployment?"). library: Python library to search documentation for. version: Optional Library version (e.g., "4.46.1"). Defaults to detected library version if not specified. top_k: Optional number of top matching documents to return. Defaults to 10.

Returns: A list of dictionaries, each containing document path and corresponding content.

Example Usage: # Search Python docs for Transformers python_get_documentation(query="what is a transformers mlm token", library="transformers", version="4.46.1")

Notes:

• This tool automatically loads or builds a RAG (Retrieval-Augmented Generation) index for the specified version.
• If an index is not found locally, the tool will fetch and index the documentation before responding.
• You should call this function for any question that needs project documentation context.