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dreamiurg

Datadog MCP Server

by dreamiurg

get_error_tracking_issue

Retrieve detailed information about a specific Datadog error tracking issue using its unique ID. Understand error context for faster debugging.

Instructions

Get details of a Datadog error tracking issue (user-facing error/exception) by ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_idYesError tracking issue ID
Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only describes the action as 'Get details,' which implies a read operation, but it does not confirm idempotency, permissions, rate limits, or error behavior. The mention of 'user-facing error/exception' adds minimal behavioral context.

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 a single, efficient sentence (15 words). It conveys the core purpose without any unnecessary words or repetition. Every part earns its place, and the structure is front-loaded with the action and resource.

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

Completeness2/5

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

Given the tool's simplicity (one parameter, no output schema), the description is minimal. It does not specify what 'details' includes (e.g., status, stack traces, timestamps). Without an output schema, the agent lacks information about the return value structure, making it incomplete for effective use.

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?

Schema description coverage is 100% (one parameter with a clear description). The description adds no extra meaning beyond 'by ID,' which mirrors the schema. Since the schema already documents the parameter adequately, the description provides no additional semantics beyond the baseline.

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

Purpose5/5

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

The description uses a specific verb ('Get details') and clearly identifies the resource ('Datadog error tracking issue'). It distinguishes from sibling tools like search_error_tracking_issues (search) and search-error-tracking-events (events) by focusing on a single resource and retrieval by ID. The parenthetical '(user-facing error/exception)' adds specificity.

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 implies usage when you have an issue ID and need details, but it does not explicitly state when to use this tool versus alternatives. No 'when not to use' or references to sibling tools are provided. The context of siblings (search functions) provides some implicit guidance, but explicit guidelines are missing.

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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