Skip to main content
Glama
nullmastermind

mcp-feedback-enhanced-gw

get_system_info

Retrieve system environment details in JSON format. Use it to inspect current system configuration and environment variables.

Instructions

Get system environment information

Returns: str: System information in JSON format

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 must fully disclose behavioral traits. It mentions that the return value is a JSON string, but it omits whether the operation is read-only, any required permissions, or potential side effects. This lack of disclosure is a notable gap for a tool with zero annotation coverage.

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 succinct and front-loaded, with the core purpose stated first and return details following. It contains no extraneous content and is appropriately sized for a simple, no-argument tool.

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

Completeness4/5

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

For a tool with no parameters and an output schema, the description covers the essential information: it retrieves system info and returns it as JSON. It does not specify the exact fields or scope of 'system information', but the output schema likely provides that detail. A brief mention of data scope or usage context would make it more complete, but it is largely sufficient for its simplicity.

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 zero parameters, which sets a baseline of 4. The description implicitly confirms that no inputs are needed, and the empty schema corroborates this. No additional parameter semantics are required.

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 tool retrieves system environment information, using a specific verb ('Get') and resource. It is well-differentiated from the sibling tool 'interactive_feedback', which serves a completely different purpose. Even though the name already implies this, the added return format detail strengthens clarity.

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, such as conditions, prerequisites, or comparisons with 'interactive_feedback'. It simply states what it does, leaving the agent without context for selecting this tool over others.

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/nullmastermind/mcp-feedback-enhanced'

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