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Glama

List models running on this machine

local_models

List running and stopped local AI model hosts with their served models, and get start commands for offline servers.

Instructions

Report the local model hosts (Ollama at :11434, llama-server at :8080, plus anything configured in /config.json) with the models each one serves. A host that is not running is reported as such, with the command that would start it. Costs nothing and probes nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden, and it does well: it discloses that non-running hosts are reported with the command to start them, and it explicitly states the operation is free of side effects ('Costs nothing and probes nothing'). It does not detail exact output formatting, but covers the key behavioral characteristics an agent would need.

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?

The description is three tight sentences: the first states the core deliverable, the second explains the non-running host behavior, and the third gives a safety guarantee. There is no wasted language, and important information is front-loaded.

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 zero-parameter listing tool with no output schema, the description is thorough. It specifies the sources of hosts (default endpoints and config file), what is reported per host (models served, running status, startup command), and the operational cost. An agent can predict the tool's behavior and results with confidence.

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?

The tool has zero parameters, so the baseline of 4 applies. The description rightly spends no space on parameters, and the schema already fully covers this trivial aspect with an empty properties object.

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 uses specific action verbs ('Report', 'List') and identifies a precise resource: local model hosts including named defaults and a config file. The scope is concrete and the tool is clearly distinguished from all unrelated siblings by its unique subject matter.

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?

The description establishes clear context for when the tool is relevant: checking local model hosts and their running status. It does not explicitly name alternatives or exclusions, but no sibling tool serves a similar purpose, so the absence of explicit routing is acceptable. The added 'Costs nothing and probes nothing' provides implicit guidance that this is a safe, low-risk tool to invoke.

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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