Calculates 24-hour uptime SLA percentages and average latency statistics across all monitors.
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": "read_uptime_statistics"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description contributes the meaningful extra detail that results are computed aggregates over a rolling 24-hour window rather than raw samples, which goes beyond the annotations, but it says nothing about how monitors with no data or partial availability are treated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with the aggregation, the metric types, the time window and the scope all front-loaded; no filler, no restatement of the name. Every clause carries information an agent needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters and no output schema, the description must carry the return semantics, and it does name the two returned statistics and the 24-hour window. It stops short of clarifying whether results are a single aggregate or a per-monitor breakdown, which is the one gap an agent would still want covered for a reporting tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters and the description adds no parameter semantics, which is the correct baseline for a no-argument tool. Schema coverage is 100% and there is nothing for the description to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a specific verb and resource: 'Calculates 24-hour uptime SLA percentages and average latency statistics.' The scope ('across all monitors', '24-hour') also implicitly distinguishes it from per-object siblings like read_monitor_status or get_monitor_history, though no sibling is named explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied by the scope phrase 'across all monitors' and the 24-hour window; the description never states when to pick this over read_monitor_status or get_monitor_history, nor any exclusions or prerequisites. An agent can infer it is the aggregate view, but that inference is left to the reader.
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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