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PhialsBasement

GitHub MCP Server Plus

get_issue

Retrieve detailed information about a specific issue in a GitHub repository by providing the repository owner, repository name, and issue number.

Instructions

Get details of a specific issue in a GitHub repository.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYes
repoYes
issue_numberYes

Implementation Reference

  • The main handler for the 'get_issue' tool in the switch statement of CallToolRequestSchema. It validates input using GetIssueSchema, calls the helper function, and returns the issue details.
    case "get_issue": {
      const args = issues.GetIssueSchema.parse(request.params.arguments);
      const issue = await issues.getIssue(args.owner, args.repo, args.issue_number);
      return {
        content: [{ type: "text", text: JSON.stringify(issue, null, 2) }],
      };
    }
  • Zod schema defining the input parameters for the 'get_issue' tool: owner, repo, and issue_number.
    export const GetIssueSchema = z.object({
      owner: z.string(),
      repo: z.string(),
      issue_number: z.number(),
    });
  • index.ts:153-157 (registration)
    Registration of the 'get_issue' tool in the ListToolsRequestHandler, including name, description, and input schema reference.
    {
      name: "get_issue",
      description: "Get details of a specific issue in a GitHub repository.",
      inputSchema: zodToJsonSchema(issues.GetIssueSchema)
    }
  • Helper function that performs the actual GitHub API request to fetch the issue details.
    export async function getIssue(owner: string, repo: string, issue_number: number) {
      return githubRequest(`https://api.github.com/repos/${owner}/${repo}/issues/${issue_number}`);
    }
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 states the action ('Get details') but does not disclose behavioral traits like authentication needs, rate limits, error handling, or what details are returned. For a read operation with zero annotation coverage, this is a significant gap in transparency.

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 that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with every part earning its place.

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 complexity (3 required parameters), lack of annotations, and no output schema, the description is incomplete. It does not explain return values, error cases, or usage context, making it inadequate for effective tool selection and invocation by an AI agent.

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

Parameters2/5

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

Schema description coverage is 0%, so the schema provides no parameter details. The description does not add any meaning beyond the parameter names (owner, repo, issue_number), such as explaining what these represent (e.g., GitHub username, repository name, issue ID) or their formats. It fails to compensate for the low coverage.

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 verb ('Get details') and resource ('specific issue in a GitHub repository'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'list_issues' or 'search_issues', which would require a more specific scope or distinction.

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 no guidance on when to use this tool versus alternatives such as 'list_issues' for multiple issues or 'search_issues' for filtered searches. It lacks explicit context, prerequisites, or exclusions, leaving usage decisions to inference.

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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