jira-creator

Create JIRA issues (stories, bugs, epics, spikes, tasks) quickly using standardized templates and optional AI-enhanced descriptions.

⚡ Quick Start (Within 30 Seconds)

📝 Create your config file and enable autocomplete

This step consists in creating a configuration file and activating autocomplete. Replace the placeholders with your actual data.

mkdir -p ~/.bashrc.d
cat <<EOF > ~/.bashrc.d/jira.sh
export JPAT="your_jira_personal_access_token"
export AI_PROVIDER=openai
export AI_API_KEY=sk-...
export AI_MODEL="gpt-4o-mini"
export JIRA_URL="https://issues.redhat.com"
export PROJECT_KEY="AAP"
export AFFECTS_VERSION="aa-latest"
export COMPONENT_NAME="analytics-hcc-service"
export PRIORITY="Normal"
export JIRA_BOARD_ID=21125

# Enable autocomplete
eval "$(/usr/local/bin/rh-issue --_completion | sed 's/rh_jira.py/rh-issue/')"
EOF

source ~/.bashrc.d/jira.sh

🔗 Link the command-line tool wrapper

This step involves making the wrapper shell script executable and linking it to a directory on your path.

chmod +x jira_creator/rh-issue-wrapper.sh
sudo ln -s $(pwd)/jira_creator/rh-issue-wrapper.sh /usr/local/bin/rh-issue

🚀 Run it

This is how you use the tool to create a story. Replace the placeholder with your actual data.

rh-issue create story "Improve onboarding experience"

🧪 Usage & Commands

🆕 Create Issues

You can create various types of issues using the following commands. Replace the placeholders with your actual data.

rh-issue create bug "Fix login crash"
rh-issue create story "Refactor onboarding flow"
rh-issue create epic "Unify frontend UI" --edit
rh-issue create spike "Evaluate GraphQL support" --dry-run

You can further customize your command with --edit to use your $EDITOR, and --dry-run to print the payload without creating the issue.

🔁 Change Issue Type

You can change the type of an existing issue with the following command. Replace the placeholders with your actual data.

rh-issue change AAP-12345 story

🔁 Migrate Issue

You can migrate an existing issue with the following command. Replace the placeholders with your actual data.

rh-issue migrate AAP-54321 story

✏️ Edit Description

You can edit the description of an existing issue with the following command. Replace the placeholders with your actual data.

rh-issue edit AAP-98765
rh-issue edit AAP-98765 --no-ai

🧍 Unassign Issue

You can unassign an existing issue with the following command. Replace the placeholders with your actual data.

rh-issue unassign AAP-12345

📋 List Issues

You can list issues with the following command. You can customize your command with --project, --component, and --user options. Replace the placeholders with your actual data.

rh-issue list
rh-issue list --project AAP --component api --user jdoe

🏷️ Set Priority

You can set the priority of an existing issue with the following command. Replace the placeholders with your actual data.

rh-issue set-priority AAP-123 High

📅 Sprint Management

You can manage sprints with the following commands. Replace the placeholders with your actual data.

rh-issue set-sprint AAP-456 1234
rh-issue remove-sprint AAP-456
rh-issue add-sprint AAP-456 "Sprint 33"

🚦 Set Status

You can set the status of an existing issue with the following command. Replace the placeholders with your actual data.

rh-issue set-status AAP-123 "In Progress"

🤖 AI Provider Support

You can plug in different AI providers by setting AI_PROVIDER.

We can use ollama for the management for different models

mkdir -vp ~/.ollama-models
docker run -d -v ~/.ollama-models:/root/.ollama -p 11434:11434 ollama/ollama

✅ OpenAI

Setup for using OpenAI as AI provider.

export AI_PROVIDER=openai
export AI_API_KEY=sk-...
export AI_MODEL=gpt-4  # Optional

🦙 LLama3

Setup for using LLama3 as AI provider.

docker compose exec ollama ollama pull LLama3
export AI_PROVIDER=LLama3
export AI_URL=http://localhost:11434/api/generate
export AI_MODEL=LLama3

🧠 DeepSeek

Setup for using DeepSeek as AI provider.

docker compose exec ollama ollama pull deepseek-r1:7b
export AI_PROVIDER=deepseek
export AI_URL=http://localhost:11434/api/generate
export AI_MODEL=http://localhost:11434/api/generate

🖥 GPT4All

Setup for using GPT4All as AI provider.

pip install gpt4all
export AI_PROVIDER=gpt4all
# WIP

🧪 InstructLab

Setup for using InstructLab as AI provider.

export AI_PROVIDER=instructlab
export AI_URL=http://localhost:11434/api/generate
export AI_MODEL=instructlab
# WIP

🧠 BART

Setup for using BART as AI provider.

export AI_PROVIDER=bart
export AI_URL=http://localhost:8000/bart
# WIP

🪫 Noop

Setup for using Noop as AI provider.

export AI_PROVIDER=noop

🛠 Dev Setup

To set up your development environment, run the following command.

pipenv install --dev

Testing & Linting

Use the following commands for testing, linting, and formatting respectively.

make test
make lint
make format  # autofix formatting

⚙️ How It Works

• Loads field definitions from .tmpl files under templates/
• Uses TemplateLoader to generate Markdown descriptions
• Optionally applies AI cleanup for readability and structure
• Sends to JIRA via REST API (or dry-runs it)

📜 License

This project is licensed under the Apache License.