Extract all unique service names from Datadog logs by specifying a time range and optional query filter to identify services in your logs.
Extract all unique service names from logs
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | End time in epoch seconds | |
| from | Yes | Start time in epoch seconds | |
| limit | No | Maximum number of logs to search through. Default is 1000. | |
| query | No | Optional query filter for log search | * |
Changes observed during successful MCP inspections.
v1.8.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. 'Extract' implies a read operation, but the description does not state whether it is read-only, what permissions are needed, how the 'limit' default of 1000 affects completeness, or whether the result is exhaustive despite saying 'all unique'.
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, front-loaded sentence with no redundant or filler text. It is appropriately sized for the tool's simplicity.
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?
For a simple tool with fully documented parameters, the description adequately implies the return value as a list of unique service names. However, without annotations or an output schema, it omits important context such as how the 'limit' constrains the search and what the exact return structure looks like.
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?
Schema description coverage is 100%, so the input schema already explains 'from', 'to', 'limit', and 'query'. The description adds no parameter-specific semantics beyond what the schema provides, which is the baseline expectation at full coverage.
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 a specific verb ('Extract') and resource ('all unique service names from logs'), which clearly distinguishes the outcome from sibling tools like get_logs. It could be slightly sharper by naming the log-retrieval alternative, but the operation is understandable without opening the schema.
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: the required 'from'/'to' parameters and 'from logs' phrase suggest it is for discovering service names within a time window. There is no explicit when-to-use/when-not-to-use guidance or comparison to alternatives such as get_logs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.