gh-issue-create

A command that turns a written request into a structured GitHub issue draft after examining the project and its repository details.

In plain words
What is it for?
Use it to create clearer GitHub issue content from a description, including implementation structure and information about the current codebase.
Why use it?
It removes the need to manually work out the issue’s requirements, test cases, expected results, edge cases, and relevant code. It does not change code.

Command for Cursor

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/ivangrynenko/cursorrules/gh-issue-create
Clone the repo
git clone --depth 1 https://github.com/ivangrynenko/cursorrules

Made for: Cursor.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,548 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01548
Opus 5 $0.00000 $0.00774
Sonnet 5 $0.00000 $0.00310
Haiku 4.5 $0.00000 $0.00155

Measured 2d ago against content hash e0cc601c6d19, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gh-issue-create scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/commands/gh-issue-create.md · 241 lines

How it starts

The opening of the file, as written. The whole thing — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Custom Command: GitHub Issue Create

Command Usage

/gh-issue-create <description>

Everything after /gh-issue-create is treated as a single argument containing the user's description of what they want to achieve.

Instructions

You are implementing a command that intelligently creates GitHub issues based on user descriptions. This task must avoid any code changes.

Think harder and follow these steps thoroughly:

1. Parse and Understand Context

  • Extract Requirements: Identify core functionality from the original request, accept the full text after the command as the user's description, analyse the current working directory to understand the project context; Identify the Git repository and its remote origin.
  • Define Test Cases: Create specific, measurable test scenarios
  • Specify Expected Outcomes: Clear success and failure criteria
  • Structure for Implementation: Organize prompt for red-green-refactor cycle
  • Include Edge Cases: Don't forget boundary conditions and error scenarios

2. Codebase Analysis

  • Explore the relevant parts of the codebase mentioned in the description
  • Look for:
    • Related existing code
    • Configuration files
    • Documentation (README, docs/, wiki references)
    • Similar patterns or implementations
    • Dependencies that might be affected

3. Issue Classification

Determine the issue type based on the description:

  • Bug: Something is broken or not working as expected
  • Feature: New functionality that doesn't exist
  • Enhancement: Improvement to existing functionality
  • Task: Technical work, refactoring, or maintenance

4. TDD Prompt Structure

1. Objective Statement

Clear, concise description of what needs to be built

2. Test Specifications
GIVEN: [Initial state/context]
WHEN: [Action performed]
THEN: [Expected outcome]

5. Break Down Into Tasks

Decompose the description into specific, actionable tasks:

  • Each task should be atomic and testable
  • Think to consider technical dependencies
  • Include both implementation and testing tasks
  • Think about documentation updates needed

Read the full file on GitHub · 241 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 241 lines · 0 tokens per session scan A e0cc601c6d19

Subscribe to this mod's changes

gh-issue-create is a command published in the GitHub repository ivangrynenko/cursorrules (88 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,548 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.