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ollama_list_models

Read-onlyIdempotent

List all installed Ollama models on your local machine and check their memory load status to discover available model names for chat, generation, or model info queries.

Instructions

List all Ollama models installed on the local machine with their memory load status. Use this tool to discover available model names before calling ollama_chat, ollama_generate, or ollama_show_model. Do not use this to check if the Ollama daemon is running — use ollama_health instead. Behavior: Read-only, idempotent, safe to retry. No authentication required. No rate limits. Returns an empty models array if no models are installed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYesAll locally installed models. Empty array if none are installed.
Behavior5/5

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

Description adds context beyond annotations: 'No authentication required. No rate limits. Returns an empty models array if no models are installed.' This fully discloses behavior and aligns with annotations (readOnlyHint, idempotentHint).

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?

Three concise sentences each serving a distinct purpose: function, usage guidance, and behavioral note. No redundant 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?

For a simple list tool with good annotations and an output schema, the description covers all necessary aspects: purpose, when to use, behavior, and return states. Complete for agent decision-making.

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?

Tool has 0 parameters, baseline is 4. Description clarifies no input needed, and schema is empty. No further parameter detail required.

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?

Description clearly states verb 'List' and resource 'Ollama models installed on the local machine with their memory load status.' It distinguishes from sibling tools by specifying its role in discovering model names before using other tools.

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 advises when to use (before ollama_chat, ollama_generate, etc.) and when not to use (for checking daemon status, recommends ollama_health instead). Also notes idempotency and safe retry.

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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