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dreamiurg

Datadog MCP Server

by dreamiurg

search-error-tracking-events

Search error groups across services with counts, first/last seen, and affected services to identify production errors and new issues.

Instructions

Search Error Tracking events across services. Use for 'what errors are happening in production', 'error groups for payment service', 'new errors this week'. Returns error groups with counts, first/last seen, and affected services.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNo
sortNoSort order
pageNo
limitNoMaximum events to return
Behavior3/5

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

The description discloses the return structure (error groups with counts, first/last seen, affected services), which is helpful. However, it does not mention pagination, rate limits, or authentication, and there are no annotations to supplement these aspects. The transparency is adequate but not comprehensive.

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?

The description is very concise with three sentences, front-loading the purpose, followed by use cases and output description. Every sentence is informative and without redundancy, achieving high efficiency.

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?

While the description covers the main purpose and output, it lacks details on parameter usage, pagination, and differentiation from similar tools. Given the tool has nested parameters and no output schema, the description leaves some gaps for a complete understanding.

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?

With 50% schema description coverage, the description adds minimal parameter insight beyond the schema. It provides example queries but does not explain how to construct the filter or handle pagination, so it does not significantly enhance understanding of the parameters.

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 clearly states 'Search Error Tracking events across services' and provides concrete examples, making the purpose clear. However, it does not differentiate from the sibling tool 'search_error_tracking_issues', which likely focuses on a different aspect, thus not achieving a top score.

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

Usage Guidelines4/5

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

The description gives practical use case examples ('what errors are happening in production', 'error groups for payment service'), which provide context. However, it does not mention when not to use this tool or alternatives, missing explicit exclusions.

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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