Retrieve SLO corrections from Datadog to maintain accurate service level objective tracking and performance monitoring.
Get an SLO correction.
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": "get_slo_correction"
}
}| 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 carries the full burden of behavioral disclosure. 'Get an SLO correction' implies a read operation but doesn't specify whether it retrieves a single correction by ID, requires authentication, has rate limits, or what the output format might be. The description provides no behavioral context beyond the basic verb.
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?
While the description is brief ('Get an SLO correction'), this brevity represents under-specification rather than effective conciseness. The single sentence fails to convey necessary context about what the tool does, making it inefficient despite its short length. Every sentence should earn its place, and this one doesn't provide enough value.
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 complexity implied by the sibling tools (multiple SLO correction operations) and the lack of annotations, output schema, and meaningful description, this is completely inadequate. The description doesn't explain what an SLO correction is, how it's identified, what data is returned, or how it differs from similar tools, leaving the agent with insufficient information to use it correctly.
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 has 0 parameters with 100% schema description coverage (empty schema). With no parameters to document, the description doesn't need to add parameter semantics. The baseline for 0 parameters is 4, as there's no parameter information to provide beyond what the schema already indicates (none).
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 'Get an SLO correction' is a tautology that essentially restates the tool name 'get_slo_correction'. It provides a verb ('Get') and resource ('SLO correction') but lacks specificity about what an SLO correction is or what this retrieval entails. It doesn't distinguish from sibling tools like 'get_slo_corrections_v1' or 'get_slo_corrections_v1_2'.
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?
The description provides no guidance on when to use this tool versus alternatives. There are multiple sibling tools related to SLO corrections (e.g., 'get_slo_corrections_v1', 'update_slo_correction', 'delete_slo_correction'), but the description offers no context about when this specific 'get' operation is appropriate versus the others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.