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Sentry MCP Server

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by getsentry

resolve_short_id

Retrieve issue details, project context, and status by mapping short IDs like PROJECT-123 to comprehensive Sentry data for debugging and monitoring.

Instructions

Retrieve details about an issue using its short ID. Maps short IDs to issue details, project context, and status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
organization_slugYesThe slug of the organization the issue belongs to
short_idYesThe short ID of the issue to resolve (e.g., PROJECT-123)
formatNoOutput format (default: markdown)markdown

Implementation Reference

  • Schema for the ShortIdResolutionResponse, which defines the output structure for resolving a short ID to Sentry group/issue details, including project and organization info.
    export interface ShortIdResolutionResponse {
      group: {
        annotations: any[];
        assignedTo: any | null;
        count: string;
        culprit: string;
        firstSeen: string;
        hasSeen: boolean;
        id: string;
        isBookmarked: boolean;
        isPublic: boolean;
        isSubscribed: boolean;
        lastSeen: string;
        level: string;
        logger: string | null;
        metadata: {
          title: string;
        };
        numComments: number;
        permalink: string;
        project: {
          id: string;
          name: string;
          slug: string;
        };
        shareId: string | null;
        shortId: string;
        status: string;
        statusDetails: Record<string, any>;
        subscriptionDetails: any | null;
        title: string;
        type: string;
        userCount: number;
      };
      groupId: string;
      organizationSlug: string;
      projectSlug: string;
      shortId: string;
    }
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 of behavioral disclosure. It mentions what gets retrieved ('issue details, project context, and status') but lacks critical information: whether this is a read-only operation, authentication requirements, rate limits, error handling, or response format details. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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

Conciseness4/5

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

The description is concise and front-loaded, stating the core purpose in the first sentence. The second sentence adds useful context about what details are retrieved. Both sentences earn their place, with no wasted words, though it could be slightly more structured (e.g., bullet points for retrieved details).

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 no annotations and no output schema, the description is incomplete for a tool with 3 parameters. It covers the basic purpose but misses behavioral traits (e.g., safety, auth), usage context vs. siblings, and output details. For a retrieval tool in a complex environment with many siblings, this leaves the agent under-informed about how to effectively use it.

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%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema: it implies the 'short_id' format (e.g., 'PROJECT-123') but doesn't elaborate on 'organization_slug' or 'format' usage. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

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 the tool's purpose: 'Retrieve details about an issue using its short ID.' It specifies the verb ('Retrieve'), resource ('issue details'), and scope ('short ID'). However, it doesn't explicitly differentiate from sibling tools like 'get_sentry_issue' or 'list_project_issues', which might also retrieve issue details through different mechanisms.

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

Usage Guidelines2/5

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

The description provides minimal guidance: it implies usage when you have a short ID (e.g., 'PROJECT-123'), but offers no explicit when-to-use vs. alternatives, prerequisites, or exclusions. For instance, it doesn't clarify when to use this tool over 'get_sentry_issue' or other issue-related siblings, leaving the agent to guess based on parameter differences alone.

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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