Skip to main content
Glama

happy_list_machines

Retrieve registered machines with their IDs, hostnames, platforms, and activity status to manage AI coding sessions across multiple devices.

Instructions

List all machines registered with Happy. Returns machine IDs, hostnames, platforms, and activity status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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. It states it 'Returns machine IDs, hostnames, platforms, and activity status' which covers output content, but lacks behavioral details like whether it's paginated, rate-limited, requires authentication, or has any side effects. For a read operation with zero annotation coverage, this is insufficient.

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 a single, efficient sentence that front-loads the core purpose ('List all machines registered with Happy') and adds useful detail about return values. Every word earns its place with zero waste.

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?

For a simple list tool with no parameters and no output schema, the description adequately covers purpose and return data. However, without annotations or output schema, it should ideally mention behavioral aspects like pagination or authentication requirements to be fully complete.

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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary information.

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 the verb ('List') and resource ('all machines registered with Happy'), and specifies the return data (machine IDs, hostnames, platforms, activity status). It distinguishes from siblings like happy_list_sessions and happy_list_environment_sets by focusing on machines rather than sessions or environment sets.

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 for retrieving machine information, but provides no explicit guidance on when to use this tool versus alternatives like happy_list_sessions or happy_list_environment_sets. No prerequisites, exclusions, or comparative context are mentioned.

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/zhigang1992/happy-server-mcp'

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