Modify service level objectives to maintain performance standards and ensure monitoring accuracy in Datadog.
Update the specified service level objective object.
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": "update_slo"
}
}| 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 full burden. It implies a mutation ('update') but doesn't disclose behavioral traits such as required permissions, whether changes are reversible, rate limits, or what happens if the SLO doesn't exist. This is a significant 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 a single, efficient sentence that directly states the tool's purpose without fluff. It's appropriately sized for a tool with no parameters, though it could be more informative by adding context about the SLO object or update scope.
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 of updating an SLO (a mutation operation), the description is incomplete. No annotations exist to cover safety or behavior, no output schema is provided, and the description lacks details on what can be updated, error conditions, or response format. This leaves the agent under-informed for a potentially impactful operation.
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, so no parameters need documentation. The description doesn't add param details, but that's unnecessary here. Baseline is 4 for 0 params, as the schema fully covers the absence of parameters.
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 states the verb 'update' and the resource 'service level objective object', which clarifies the basic action. However, it's vague about what specific aspects can be updated (e.g., thresholds, time windows, name) and doesn't differentiate from sibling tools like 'slos_update' or 'update_slo_correction', leaving ambiguity about scope.
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?
No guidance is provided on when to use this tool versus alternatives. There are multiple sibling tools related to SLOs (e.g., 'slos_update', 'update_slo_correction', 'create_slos', 'delete_slo'), but the description offers no context on prerequisites, distinctions, or exclusions, leaving the agent to guess based on naming alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.