Cancel scheduled downtime periods in Datadog to resume monitoring and alerting for systems or services.
Cancel downtime
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": "downtimes_cancel"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. 'Cancel downtime' implies a destructive mutation (canceling something), but it fails to describe any behavioral aspects: whether it requires specific permissions, what happens upon cancellation (e.g., immediate resumption of monitoring), if it's reversible, or what the response looks like. This is a critical gap for a mutation 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just two words, which could be seen as efficient. However, it is under-specified rather than appropriately concise—it lacks necessary context for a mutation tool. While front-loaded, it fails to provide any useful information beyond the name, making it more of a placeholder than a helpful description.
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?
Given the tool's complexity (a mutation operation with potential side effects), the absence of annotations, no output schema, and a minimal description, this is highly incomplete. The description does not compensate for the lack of structured data, leaving the agent without critical information on behavior, outcomes, or usage context, making it inadequate for safe and correct invocation.
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 input schema has 0 parameters with 100% description coverage, meaning there are no parameters to document. The description does not need to add parameter semantics, and it appropriately avoids mentioning any. Given the baseline of 4 for zero parameters, this is adequate as the schema fully covers the absence of inputs.
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 'Cancel downtime' is essentially a tautology that restates the tool name 'downtimes_cancel' without adding meaningful context. It specifies the verb 'cancel' and resource 'downtime', but lacks any detail about what downtime refers to (e.g., monitoring downtime, scheduled maintenance) or scope, making it vague and minimally informative beyond the name itself.
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?
There is absolutely no guidance on when to use this tool versus alternatives. The description does not mention prerequisites (e.g., needing an existing downtime to cancel), differentiate from sibling tools like 'downtimes_create' or 'downtimes_list', or specify any context for invocation. This leaves the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.