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Glama

ollama_show_model

Read-onlyIdempotent

Inspect detailed metadata of an installed Ollama model including architecture, license, and parameters before using it for chat or generation. Read-only and idempotent.

Instructions

Retrieve detailed metadata about a specific installed Ollama model. Use this tool to inspect a model's architecture, license, quantization level, prompt template, and default parameters before using it with ollama_chat or ollama_generate. Do not use this to list all models — use ollama_list_models instead. Do not use this to download new models — use ollama_pull_model instead. Prerequisites: The model must already be installed locally (verify with ollama_list_models). Behavior: Read-only, idempotent, safe to retry. No authentication required. No rate limits. Returns the same metadata for the same model every time. On model-not-found error, returns an error object without throwing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesExact Ollama model identifier to inspect (e.g., 'llama3.1:8b', 'mistral:latest'). Must match a 'name' from ollama_list_models output. If unsure which models are installed, call ollama_list_models first.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoError message if the model was not found. Only present on failure.
detailsNoModel architecture details.
templateNoGo template string used for prompt formatting.
modelfileNoThe full Modelfile content defining this model's configuration.
parametersNoRuntime parameter defaults (e.g., temperature, context length) as a formatted string.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, idempotent, non-destructive. Description adds read-only, idempotent, safe to retry, no auth, no rate limits, consistent returns, and error handling behavior. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise, well-structured, front-loaded with purpose, bullet-like guidelines, every sentence adds value. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, usage, prerequisites, behavior, error handling. With good annotations and output schema, nothing missing. Complete for a simple inspection tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. Description adds value by explaining the parameter is an exact identifier from ollama_list_models, provides examples, and suggests calling that tool first if unsure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it retrieves detailed metadata about a specific installed Ollama model, including architecture, license, etc. It clearly distinguishes from sibling tools like ollama_list_models and ollama_pull_model.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use (before ollama_chat/generate), when not to use (listing or downloading models), prerequisites (model installed), and alternative tool names are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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