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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
SYSTEMONE_MODELNoDefault model when the tool call omits `model`. Any of `nimble` / `tev` / `clef` / `jev` / `kev` / `laya`.nimble
SYSTEMONE_API_KEYNoOptional. TypeSafe cloud / Kev with key / Laya with `LAYA_API_KEY`. Sent as `Authorization: Bearer <key>`.
SYSTEMONE_BASE_URLNoMust start with `http://` or `https://`. Ollama default `http://localhost:11434`.http://localhost:11434

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
systemone_evaluateC

Answer typed choice/score/noul questions with a System One model (jev/nimble/kev/tev/laya).

systemone_list_modelsB

List available System One models on the configured backend.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.2/5.0

Scored across 2 tools

Disambiguation5/5

The two tools serve clearly distinct purposes: one enumerates available models and the other runs an evaluation with a chosen model. There is no overlap in resource or action, so an agent cannot realistically confuse them.

Naming Consistency4/5

Both names share the 'systemone_' snake_case prefix, which is predictable and readable. The minor deviation is that 'evaluate' is a bare verb without a noun object unlike 'list_models', but the set still feels coherent.

Tool Count3/5

Two tools is thin even for a narrow evaluation-model domain; there is no separate model-detail, configuration, or result-retrieval tool. It is borderline rather than mismatched, since the core discover-then-evaluate flow is present.

Completeness3/5

The surface covers the minimal loop of listing models and evaluating a question, but lacks supporting operations such as fetching model metadata, setting backend configuration, or retrieving/batching prior evaluations. Agents can work around this only by relying on external configuration.

Maintenance

ActivityMaintained
ResponsivenessNo issues