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Percival Ubuntu

Percival Ubuntu

by bill-kopp-ai-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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ubuntu_get_server_status

Check server health, active policies, and tool metrics. Use as first diagnostic when automations degrade, with optional detailed view for extended timing and full policy lists.

Instructions

Return server health, effective policy snapshot, and tool metrics.

Use this as the first diagnostic tool when automations degrade.

Args: detailed: If True, includes extended timing fields and full policy lists; if False, returns compact observability view.

Returns: JSON string in unified {ok, data|error} contract.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ubuntu_get_server_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
detailedNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the output contract ('JSON string in unified {ok, data|error} contract') and parameter behavior for the detailed flag. However, it does not explicitly state whether the tool is read-only, requires special permissions, or has performance implications, which would be more transparent for a status 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 tightly structured and front-loaded. The core purpose appears in the first sentence, followed by a one-line usage directive, then a concise Args/Returns breakdown. No sentence is wasted.

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

Completeness5/5

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

The tool is simple with one optional parameter and an output schema is present per context signals. The description covers what the tool returns, the parameter's effect, and the recommended use scenario. Nothing critical is missing for an agent to invoke it correctly.

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 schema only provides the type and default for the `detailed` parameter, with 0% schema description coverage. The description adds meaningful semantics: if True it includes extended timing fields and full policy lists, if False it returns a compact view. However, it does not explain the behavior when `detailed` is null, which is a permitted default value.

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 and resource: 'Return server health, effective policy snapshot, and tool metrics.' It clearly differentiates this diagnostic tool from siblings like ubuntu_execute_command or ubuntu_read_file, and even frames its role as the first diagnostic tool.

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

Usage Guidelines4/5

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

The description explicitly tells the agent when to use it: 'Use this as the first diagnostic tool when automations degrade.' It does not explicitly mention alternatives or when not to use it, but the usage context is clear and actionable.

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

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