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Glama

System Health Check

system_health_check

Assess LM Studio health for a profile: verify endpoint reachability with auto-restart recovery, check free disk space for downloads, detect stuck-loaded models, then return overall status.

Instructions

Check LM Studio health for a profile: endpoint reachability (with a one-shot lms server start autostart recovery and recheck), free disk space for downloads, and stuck-loaded-model detection. Returns an overall status (healthy/degraded/down) plus per-check sub-fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profileYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses a notable side effect: a one-shot lms server start autostart recovery and recheck, which is a behavioral trait. However, it does not disclose whether other checks have side effects, error handling, or timeouts, so transparency is partial.

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 two sentences, front-loaded with the core purpose, and lists the checks succinctly without extraneous detail. Every word serves to inform the agent about scope and return.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema, the description must explain return values. It mentions an overall status (healthy/degraded/down) and per-check sub-fields, but does not detail the sub-field structure or possible values. It also omits prerequisites or potential error conditions, leaving gaps for an agent to infer.

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?

The schema has zero description coverage for the single 'profile' parameter. The description clarifies that the check is scoped to a profile, but it does not explain what a profile is, its format, or any constraints. This adds minimal meaning beyond the parameter name.

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 states a specific verb (check) and resource (LM Studio health for a profile), and lists distinct health checks (endpoint reachability, disk space, stuck-loaded-model detection) with a clear return structure. This distinguishes it from related sibling tools like nanites_ping or get_loaded_model.

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 this tool is for a health overview of a profile, but it does not explicitly state when to use it versus alternatives or when not to use it. No exclusions or sibling references are provided, so usage guidance is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.