Skip to main content
Glama

it_ops_maintenance_cycle

Execute an IT operations maintenance cycle by providing a free-text objective and optional structured inputs through the domain agent dispatcher.

Instructions

Run the it_ops domain agent action maintenance_cycle.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
inputsNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions routing through a dispatcher under JWT/tenant/company scope, which provides some context, but does not disclose whether the action is destructive, read-only, or what side effects (if any) occur. The term 'maintenance cycle' suggests a management operation, but the behavior remains ambiguous.

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 concise with three sentences plus parameter descriptions. It is efficiently written, but the key action (first sentence) could be more front-loaded to immediately convey the core purpose. No unnecessary words.

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

Completeness2/5

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

Despite having an output schema (indicated in context signals), the description does not mention return values, output structure, or any side effects. For a tool with two parameters and no annotations, important context about when to invoke it and what to expect is missing, making it incomplete.

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 description adds meaning to both parameters beyond the schema (which only provides default values and types). It explains 'message' as a free-text objective and 'inputs' as an optional JSON string. Given 0% schema description coverage, this is helpful, but it lacks further detail such as constraints, expected format, or examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs a specific domain agent action ('maintenance_cycle') with a proper verb-resource combination. However, it does not distinguish this tool from numerous sibling tools in the it_ops domain, such as it_ops_deployment or it_ops_analysis_review, so the uniqueness is not emphasized.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites, exclusions, or typical use cases. It merely states what the tool does without contextualizing when it is appropriate.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/RPasquale/lightbulb-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server