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GitHub MCP Server

GitHub MCP Server

create_issue

Opens a new GitHub issue (bug report, task, or improvement) in an existing repository using a title and body, so users can report problems or create tasks.

Instructions

Abre un nuevo issue (reporte de bug, tarea o mejora) en un repositorio EXISTENTE de GitHub, con título y descripción. Úsalo cuando el usuario pida reportar un problema, crear una tarea o abrir un issue.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "repo": "<repo>",
      "title": "<title>"
    },
    "name": "create_issue"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyNoDescripción detallada del issue (acepta Markdown)
repoYesNombre del repositorio donde se abrirá el issue
ownerNoUsuario u organización dueña del repositorio. Si se omite, se usa el usuario autenticado
titleYesTítulo del issue

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It discloses the prerequisite that the repository must already exist, but says nothing about required permissions/scopes, whether the created issue is public, duplicate handling, or that the operation is a non-reversible mutation.

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?

Two tight sentences with the action front-loaded and the usage trigger immediately after. No filler or redundant restatement of the tool name.

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?

Parameter semantics are fully covered by the schema, and the purpose and trigger are clear. However, for a write operation with no annotations and no output schema, the definition omits permission requirements and any indication of what a successful call returns.

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 repo, owner, title, and body. The description only restates that title and description are supplied and adds no semantics about the optional owner defaulting to the authenticated user.

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?

States a specific verb and resource ("Abre un nuevo issue") plus the object it acts on (an EXISTING GitHub repository), and names the issue types it covers (bug, task, improvement). This lets an agent distinguish it from siblings like list_issues or close_issue without opening any schema.

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?

Gives clear triggering conditions: use it when the user asks to report a problem, create a task, or open an issue. It does not state when not to use it or name an alternative tool for related operations, so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.