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list_ollama_models

View available Ollama cloud models, locally pulled models, and the configured council to choose concrete options before configuring a council. Read-only listing simplifies selection.

Instructions

List the Ollama Cloud models available to put in the council, so you can offer the user a real, concrete choice instead of guessing. Returns the live ollama.com catalog (GLM, MiniMax-M3, Qwen, Kimi, DeepSeek, Nemotron, Mistral, gpt-oss, …) as daemon-ready ids, the models already pulled locally (certain to run right now), and the council that's currently configured. REACH FOR THIS the first time an Ollama council is wanted or when the user asks to configure ask_fable: call this, show the options, ask which they want, then persist the choice with configure_ollama_council. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refreshNoFetch the live ollama.com catalog + locally-pulled models. When false, only report the currently-configured council (no network).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.12.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full disclosure burden. It clearly states 'Read-only', explains that it fetches the live ollama.com catalog, notes that local models are certain to run, and describes outputs as daemon-ready ids. This goes well beyond a generic 'list' statement and covers the main behavioral and safety expectations.

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 dense sentences front-load the purpose, then describe outputs, then give the workflow. The illustrative list of model names and the rationale 'instead of guessing' add useful context without padding, and the 'Read-only' note is efficiently placed.

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 one-optional-parameter, read-only tool with no output schema, this description is complete enough: it covers when to use it, what it returns, why it matters, and the follow-up action. An agent can correctly invoke it and interpret the result categories without additional guessing.

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

Parameters3/5

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

Schema coverage is 100%, and the input schema already documents the refresh parameter's true/false behavior in detail. The description adds no meaningful parameter semantics beyond mentioning live versus currently-configured data, so the baseline of 3 applies.

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?

States a specific action ('List') and resource ('Ollama Cloud models available to put in the council'), and further specifies that it returns the live catalog, locally pulled models, and the currently configured council. The 'Ollama' and 'council' specifics clearly distinguish it from sibling listers like list_openrouter_models and list_atlas_models.

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

Usage Guidelines4/5

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

Gives an explicit trigger ('first time an Ollama council is wanted' or 'user asks to configure ask_fable') and a concrete workflow: call, show options, ask, then persist with configure_ollama_council. It does not explicitly name alternative list_*_model tools or state when not to use them, but the Ollama-specific condition makes routing fairly unambiguous.

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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