title: 'Language Models Tools' sidebar_label: 'Tools' description: 'Learn how LLMs interact with the Spice runtime.' sidebar_position: 1 pagination_prev: null pagination_next: null tags:
Spice provides tools that help LLMs interact with the runtime. To specify these tools for a Spice model, include them in its params.tools.
For a list of available tools, or how to define additional tools, see Tool Components.
The tools parameter on a model controls how tools are provided to the LLM:
| Value | Description |
|---|---|
auto | Automatically choose between direct tools and searchable registry discovery. When the number of available tools exceeds 20 and an embedding model is available, auto switches to registry-based discovery; otherwise it uses direct tools. |
all | Provide all built-in and Spicepod-configured tools directly to the LLM. |
search_registry | Use searchable registry discovery. The LLM receives tool_search and tool_invoke meta-tools instead of individual tool definitions. Requires an embedding model (see tool_embedding_model). |
<tool1>, <tool2>, ... | Provide only the named tools directly. |
For details on tool groups, see Tool Components.
When the runtime exposes many tools (multiple MCP servers, lots of dataset-bound tools, or many Functions declared with as_tool: true), passing every tool definition into every chat turn consumes a large portion of the context window and degrades selection accuracy. The Tool Registry replaces individual tool definitions with two meta-tools — tool_search and tool_invoke — backed by a hybrid search index over the runtime's tool catalog. This typically saves ~10× the per-turn tool-definition tokens for tool-heavy Spicepods.
tools: auto enables the registry automatically when there are more than 20 tools and an embedding model is configured; tools: search_registry requires it.
See Tool Registry for the full reference, including the hybrid-search algorithm, tool_search / tool_invoke parameters and response shapes, and guidance on when to prefer direct tools.
When a model requests to call a runtime tool, Spice runs the tool internally and feeds the result back to the model. The model may then request another tool call based on the result, creating a chain of tool invocations. The tool_recursion_limit parameter limits the depth of this internal recursion. By default, this limit is set to 10.
Lowering the limit can help prevent runaway tool chains in cases where a model repeatedly invokes tools without converging on a final answer.
