Search and analyze logs and events from Datadog to identify patterns, troubleshoot issues, and monitor system performance.
Search logs (events)
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": "logs_search_events"
}
}| 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. 'Search logs (events)' implies a read-only query operation, but it doesn't disclose any behavioral traits: no information about authentication needs, rate limits, pagination, return format, or whether it's a real-time or historical search. This leaves the agent with no understanding of how the tool behaves.
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 ('Search logs (events)') but this brevity results in under-specification rather than efficient communication. It's front-loaded but fails to provide necessary context, making it ineffective despite its short length.
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 a search operation with no annotations, no output schema, and many sibling tools, the description is completely inadequate. It doesn't explain what 'logs' or 'events' mean in this context, how results are returned, or any prerequisites, leaving the agent unable to use the tool effectively.
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 there are no parameters to document. The description doesn't need to add parameter semantics, and a baseline of 4 is appropriate since the schema fully covers the lack of parameters, though the description could hint at implicit filtering if any exists.
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 'Search logs (events)' states the basic action (search) and target (logs/events), but is vague about scope and differentiation. It doesn't specify what kind of logs, what time range, or how this differs from sibling tools like 'search_events' or 'get_logs_events', leaving the purpose unclear beyond the minimal.
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. With many sibling tools like 'search_events', 'get_logs_events', and 'logs_aggregate_analytics', there's no indication of when this specific search tool is appropriate, making it impossible for an agent to choose correctly without external context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.