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PhialsBasement

GitHub MCP Server Plus

create_issue

Create new issues in GitHub repositories to track bugs, features, or tasks. Specify owner, repo, title, and optional details like body, assignees, labels, or milestone.

Instructions

Create a new issue in a GitHub repository

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYes
repoYes
titleYes
bodyNo
assigneesNo
milestoneNo
labelsNo

Implementation Reference

  • MCP tool handler for 'create_issue': parses arguments using CreateIssueSchema, extracts owner/repo/options, calls issues.createIssue, and returns JSON-formatted response.
    case "create_issue": {
      const args = issues.CreateIssueSchema.parse(request.params.arguments);
      const { owner, repo, ...options } = args;
      const issue = await issues.createIssue(owner, repo, options);
      return {
        content: [{ type: "text", text: JSON.stringify(issue, null, 2) }],
      };
    }
  • index.ts:98-102 (registration)
    Registration of the 'create_issue' tool in the ListTools response, including name, description, and input schema reference.
    {
      name: "create_issue",
      description: "Create a new issue in a GitHub repository",
      inputSchema: zodToJsonSchema(issues.CreateIssueSchema),
    },
  • Input schema for create_issue tool: combines owner, repo, and CreateIssueOptionsSchema.
    export const CreateIssueSchema = z.object({
      owner: z.string(),
      repo: z.string(),
      ...CreateIssueOptionsSchema.shape,
    });
  • Core implementation: makes POST request to GitHub Issues API with provided options.
    export async function createIssue(
      owner: string,
      repo: string,
      options: z.infer<typeof CreateIssueOptionsSchema>
    ) {
      return githubRequest(
        `https://api.github.com/repos/${owner}/${repo}/issues`,
        {
          method: "POST",
          body: options,
        }
      );
    }
  • Supporting schema for issue creation options: title, body, assignees, milestone, labels.
    export const CreateIssueOptionsSchema = z.object({
      title: z.string(),
      body: z.string().optional(),
      assignees: z.array(z.string()).optional(),
      milestone: z.number().optional(),
      labels: z.array(z.string()).optional(),
    });
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation but doesn't mention permission requirements, rate limits, what happens on success/failure, or whether it's idempotent. For a write operation with zero annotation coverage, this leaves significant behavioral gaps.

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 with zero wasted words. It's appropriately sized for a basic tool description and front-loads the essential information about what the tool does.

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?

For a 7-parameter write operation with no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't explain return values, error conditions, authentication needs, or parameter semantics, leaving the agent with insufficient context to use the tool effectively.

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?

With 0% schema description coverage for all 7 parameters, the description provides no parameter information beyond what's inferred from the tool name. It doesn't explain what 'owner', 'repo', 'title', 'body', 'assignees', 'milestone', or 'labels' mean or how they should be formatted, failing to compensate for the schema's lack of descriptions.

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 action ('Create a new issue') and target resource ('in a GitHub repository'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'update_issue' or 'add_issue_comment', which would require explicit comparison to earn a 5.

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 like 'update_issue' for modifying existing issues or 'add_issue_comment' for adding comments. There's no mention of prerequisites, context, or exclusions, leaving the agent with minimal usage direction.

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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