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ShadovvSinger

Ollama_MCP_Guidance

get_running_models

Queries the Ollama API to list all running models with their details, including size and status, for monitoring active sessions.

Instructions

Get the status of currently running Ollama models.

This tool queries the Ollama API's /api/ps endpoint to retrieve information about running models,
similar to the 'ollama ps' command. It validates the response format and provides formatted output.

Args:
    None: This function does not require any parameters.

Returns:
    str: JSON-formatted string containing:
        - List of running models with their details if successful
        - Error details if the request fails or response format is invalid

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that it queries an API endpoint, validates the response, and returns a JSON-formatted string or error details. It could be more explicit about being read-only and safe, but overall it is transparent enough.

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

Conciseness4/5

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

The description is fairly concise with three short paragraphs. It front-loads the purpose and then explains internals and return format. However, some details like 'similar to the ollama ps command' could be seen as slightly redundant, but overall it is well-structured.

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?

Given no annotations, the description provides complete context: input (none), behavior (queries API, validates), and output (JSON string with list or error). With an output schema present, it does not need to detail return fields, but it still provides a useful summary. For a simple read tool, it is fully sufficient.

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, and the description explicitly states 'Args: None: This function does not require any parameters.' Since schema coverage is 100% and the description adds clarity about no inputs, a baseline of 4 is appropriate.

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 clearly states it queries the Ollama API's /api/ps endpoint to get the status of currently running models, similar to 'ollama ps'. It distinguishes itself from sibling tools like get_ollama_list (which likely lists all models) by focusing on running models.

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

Usage Guidelines3/5

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

The description implies usage is for checking running models, but does not explicitly state when to use this tool versus alternatives like get_ollama_list or other sibling tools. No exclusions or prerequisites are mentioned, leaving some ambiguity for the agent.

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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