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micaelmalta

MCP Datadog Server

by micaelmalta

search_logs

Search Datadog logs by filter query and time range, returning matching entries to debug issues and analyze application behavior.

Instructions

Search Datadog logs with filters and a time range. Returns log entries matching the query, useful for debugging and log analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesEnd time as Unix timestamp (seconds/ms) or ISO 8601 string (must be after 'from')
fromYesStart time as Unix timestamp (seconds/ms) or ISO 8601 string
limitNoMaximum number of logs to return (default: 100, max: 100)
filterYesLog filter query (e.g., "service:api status:error", "host:prod-*"). Use Datadog query syntax.
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that it returns matching log entries, which is basic. It does not mention any constraints like result ordering, pagination, or the fact that it is a read-only operation. The behavior is largely implicit from the verb 'Search' and schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences totaling 18 words. It front-loads the verb 'Search' and provides essential context. Every word is informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema covers parameters and defaults. The description captures the core function but does not differentiate from sibling log tools or explain the output format. For a simple search tool with no output schema, it is adequate but could be improved with usage guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All four parameters have descriptions in the schema (100% coverage), so the description is not required to add much. It mentions 'filters and a time range' which maps to filter, from, and to, but adds no additional semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the verb 'Search' with 'Datadog logs' as the resource, clearly indicating the action. It includes filters and time range as parameters, and states it returns matching log entries. It could better distinguish from sibling tools like aggregate_logs or get_log_details, but the core purpose is clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'useful for debugging and log analysis,' implying when to use it, but does not provide explicit guidance on when not to use it or mention alternatives such as get_log_details or aggregate_logs. This is adequate but not strong.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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