chat and complete both send text to the model and return output, so their boundary rests entirely on the chat-template distinction, which the descriptions do clarify. tokenize, models, and health are each clearly distinct from that pair and from each other.

All names are single lowercase words in a consistent casing style, which keeps them readable. However, the set mixes bare verbs (chat, complete, tokenize) with bare nouns (models, health) with no predictable verb_noun pattern.

Five tools is well-scoped for a thin wrapper over a local llama-server: two generation modes, tokenizer access, model listing, and a health probe. Each tool earns its place with no obvious redundancy.

Core inference and diagnostics are covered, but common llama-server capabilities are absent: embeddings, explicit model selection/load-unload for router mode, and detokenization. Agents can still work around these gaps but will hit dead ends for embedding workflows.