Skip to main content
Glama
Sign In
@forgespace/ui-mcp

@forgespace/ui-mcp

Official
by Forge-Space
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

manage_training

Manage ML training jobs: check prerequisites, start LoRA fine-tuning, monitor progress, cancel runs, list adapters, and view statistics.

Instructions

Manage ML training jobs for the UIForge sidecar model. Actions: check_readiness (verify training prerequisites), start_training (begin LoRA fine-tuning), get_status (check job progress), cancel_training (stop running job), list_adapters (show available adapters), get_summary (get training statistics).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "action": "<action>"
    },
    "name": "manage_training"
  }
}

Input Schema

NameRequiredDescriptionDefault
actionYesAction to perform on the training system
adapter_nameNoName of the adapter: quality-scorer, prompt-enhancer, or style-recommender

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.25.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It briefly describes each action in parentheses but fails to mention side effects, prerequisites, or consequences of mutating actions like start_training or cancel_training.

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 a single sentence that front-loads the main purpose and concisely lists actions. It is appropriately sized but could be structured as a list for clarity.

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 the tool's complexity (multiple actions) and lack of output schema, the description provides a high-level overview but lacks detail on each action's behavior, required inputs, and results. It is minimally adequate.

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 description coverage is 100%, so baseline is 3. The description does not add new information about parameters beyond what the schema provides; action values are listed but schema already includes enum descriptions.

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 identifies the tool's purpose ('Manage ML training jobs for the UIForge sidecar model') and lists specific actions. It is distinct from all sibling tools, none of which mention training.

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 by listing actions but does not provide explicit guidelines on when to use this tool versus alternatives or when to use each action. No when-not guidance is given.

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

Deploy Server

Other Tools