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Jira Automation

Organization
claude-office-skills
Jira Automation

Automate Jira project management workflows, sprint planning, issue tracking, and reporting

Overview

Publisherclaude-office-skills
Repositoryskills
Skill nameJira Automation
Stars
514
Forks
97
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by claude-office-skills on GitHub. Read the source before you install it.

Installation

Install the Jira Automation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/claude-office-skills/skills/tree/main/jira-automation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/claude-office-skills/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/jira-automation .claude/skills/claude-office-skills-jira-automation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jira Automation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Jira Automation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Jira Automation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Jira Automation

Comprehensive skill for automating Jira project management and agile workflows.

Core Workflows

1. Issue Management Pipeline

ISSUE LIFECYCLE:
┌─────────────────┐
│    Backlog      │
└────────┬────────┘
         ▼
┌─────────────────┐
│   To Do         │──────┐
└────────┬────────┘      │
         ▼               │
┌─────────────────┐      │ Blocked
│   In Progress   │◄─────┘
└────────┬────────┘
         ▼
┌─────────────────┐
│   In Review     │
└────────┬────────┘
         ▼
┌─────────────────┐
│     Done        │
└─────────────────┘

2. Automation Rules

yaml
automation_rules:
  - name: auto_assign_on_transition
    trigger:
      type: issue_transitioned
      to_status: "In Progress"
    condition:
      assignee: unassigned
    action:
      assign_to: trigger_user

  - name: add_label_on_priority
    trigger:
      type: issue_created
      priority: highest
    action:
      - add_label: "urgent"
      - send_slack: "#dev-alerts"

  - name: auto_close_subtasks
    trigger:
      type: issue_transitioned
      to_status: "Done"
      issue_type: Story
    action:
      transition_subtasks: "Done"

  - name: sla_warning
    trigger:
      type: scheduled
      cron: "0 9 * * 1-5"
    condition:
      jql: "status = 'In Progress' AND updated < -3d"
    action:
      - add_comment: "@assignee Please update this issue"
      - send_notification: assignee

Sprint Management

Sprint Planning Template

yaml
sprint_planning:
  name: "Sprint {{sprint_number}}"
  duration: 14  # days
  
  capacity_planning:
    team_size: 6
    hours_per_day: 6
    total_capacity: 504  # hours
    
  story_points:
    target: 42
    buffer: 10%  # for unplanned work
    
  ceremonies:
    - name: Sprint Planning
      day: 1
      duration: 2h
    - name: Daily Standup
      day: "daily"
      duration: 15m
    - name: Sprint Review
      day: 14
      duration: 1h
    - name: Retrospective
      day: 14
      duration: 1h

Sprint Board Configuration

yaml
board_config:
  type: scrum
  columns:
    - name: Backlog
      statuses: ["Backlog"]
    - name: To Do
      statuses: ["To Do", "Selected for Development"]
      wip_limit: null
    - name: In Progress
      statuses: ["In Progress"]
      wip_limit: 6
    - name: In Review
      statuses: ["Code Review", "QA"]
      wip_limit: 4
    - name: Done
      statuses: ["Done"]
      
  swimlanes:
    type: assignee
    show_epics: true

Issue Templates

Bug Report

yaml
bug_template:
  project: DEV
  issue_type: Bug
  fields:
    summary: "[BUG] {{title}}"
    description: |
      ## Description
      {{description}}
      
      ## Steps to Reproduce
      1. {{step1}}
      2. {{step2}}
      3. {{step3}}
      
      ## Expected Behavior
      {{expected}}
      
      ## Actual Behavior
      {{actual}}
      
      ## Environment
      - Browser: {{browser}}
      - OS: {{os}}
      - Version: {{app_version}}
      
      ## Screenshots
      {{attachments}}
    
    priority: {{severity}}
    labels: ["bug", "needs-triage"]
    components: ["{{component}}"]

Feature Request

yaml
feature_template:
  project: DEV
  issue_type: Story
  fields:
    summary: "[FEATURE] {{title}}"
    description: |
      ## User Story
      As a {{user_type}}, I want to {{action}} so that {{benefit}}.
      
      ## Acceptance Criteria
      - [ ] {{criteria1}}
      - [ ] {{criteria2}}
      - [ ] {{criteria3}}
      
      ## Technical Notes
      {{tech_notes}}
      
      ## Design Mockups
      {{mockups}}
    
    labels: ["feature", "needs-refinement"]
    story_points: null  # To be estimated

Epic Structure

yaml
epic_template:
  project: DEV
  issue_type: Epic
  fields:
    summary: "{{epic_name}}"
    description: |
      ## Overview
      {{overview}}
      
      ## Goals
      - {{goal1}}
      - {{goal2}}
      
      ## Success Metrics
      | Metric | Current | Target |
      |--------|---------|--------|
      | {{metric1}} | {{current1}} | {{target1}} |
      
      ## Timeline
      Start: {{start_date}}
      Target Completion: {{end_date}}
      
      ## Dependencies
      {{dependencies}}
      
    child_issues:
      - type: Story
        count: "auto"

JQL Queries Library

Common Queries

jql
# My open issues
assignee = currentUser() AND resolution = Unresolved ORDER BY priority DESC

# Sprint progress
project = DEV AND Sprint = "Sprint 15" ORDER BY status

# Bugs by severity
project = DEV AND type = Bug AND resolution = Unresolved 
ORDER BY priority DESC, created ASC

# Stale issues
project = DEV AND status = "In Progress" AND updated < -7d

# Ready for review
project = DEV AND status = "Code Review" AND "Code Reviewer" is EMPTY

# Release scope
fixVersion = "v2.5.0" AND resolution = Unresolved

# Team velocity
project = DEV AND type = Story AND Sprint in closedSprints() 
AND resolved >= -90d

# Blockers
project = DEV AND (priority = Blocker OR labels = blocked)
AND resolution = Unresolved

Reporting & Dashboards

Sprint Dashboard

SPRINT 15 DASHBOARD
═══════════════════════════════════════

Progress:
Day 8 of 14 │ ████████░░░░░░ 57%

Story Points:
Committed: 42
Completed: 24  │ ████████████░░░░░░░░ 57%
Remaining: 18

Burndown:
│ 42 ┤ ▪
│    │  ▪▪
│    │    ▪▪
│    │      ▪▪▪
│ 21 ┤         ▪ ← Ideal
│    │          ▪▪
│    │            ▪▪
│    │              ▪▪
│  0 ┤                ▪
└────┴────────────────────
     Day 1           Day 14

Issue Status:
To Do        ███░░░░░░░ 6
In Progress  █████░░░░░ 8
In Review    ████░░░░░░ 5
Done         █████████░ 12

Velocity Chart

TEAM VELOCITY (Last 6 Sprints)
═══════════════════════════════════════

│  50 ┤
│     │           ▓▓
│  40 ┤    ▓▓     ▓▓     ▓▓     ▓▓
│     │    ▓▓ ▓▓  ▓▓     ▓▓ ▓▓  ▓▓
│  30 ┤ ▓▓ ▓▓ ▓▓  ▓▓ ▓▓  ▓▓ ▓▓  ▓▓
│     │ ▓▓ ▓▓ ▓▓  ▓▓ ▓▓  ▓▓ ▓▓  ▓▓
│  20 ┤ ▓▓ ▓▓ ▓▓  ▓▓ ▓▓  ▓▓ ▓▓  ▓▓
│     │ ▓▓ ▓▓ ▓▓  ▓▓ ▓▓  ▓▓ ▓▓  ▓▓
│  10 ┤ ▓▓ ▓▓ ▓▓  ▓▓ ▓▓  ▓▓ ▓▓  ▓▓
│     │ ▓▓ ▓▓ ▓▓  ▓▓ ▓▓  ▓▓ ▓▓  ▓▓
│   0 ┴─────────────────────────────
       S10 S11 S12 S13 S14 S15

Average: 38 points | Trend: +5%

Integration Workflows

GitHub Integration

yaml
github_integration:
  branch_creation:
    trigger: issue_transitioned_to_in_progress
    pattern: "{{issue_type}}/{{issue_key}}-{{summary_slug}}"
    
  commit_linking:
    patterns:
      - "{{issue_key}}"
      - "#{{issue_key}}"
    action: add_comment_with_link
    
  pr_automation:
    on_pr_open:
      - transition_issue: "Code Review"
      - add_pr_link_to_issue
    on_pr_merge:
      - transition_issue: "Done"
      - add_comment: "Merged in {{pr_url}}"

Slack Integration

yaml
slack_integration:
  channels:
    dev_updates: "#dev-updates"
    alerts: "#dev-alerts"
    
  notifications:
    - event: blocker_created
      channel: alerts
      message: "🚨 Blocker: {{issue.key}} - {{issue.summary}}"
      
    - event: sprint_started
      channel: dev_updates
      message: "🏃 Sprint {{sprint.name}} has started! Goal: {{sprint.goal}}"
      
    - event: release_completed
      channel: dev_updates
      message: "🚀 Release {{version}} is live!"

Workflow Customization

Custom Workflow

yaml
workflow:
  name: Development Workflow
  statuses:
    - Backlog
    - Ready for Dev
    - In Progress
    - Code Review
    - QA
    - Ready for Release
    - Done
    
  transitions:
    - from: Backlog
      to: Ready for Dev
      name: "Refine"
      conditions:
        - story_points_set
        
    - from: Ready for Dev
      to: In Progress
      name: "Start Work"
      post_functions:
        - assign_to_current_user
        
    - from: In Progress
      to: Code Review
      name: "Submit for Review"
      validators:
        - has_linked_pr
        
    - from: Code Review
      to: QA
      name: "Pass Review"
      conditions:
        - all_reviewers_approved
        
    - from: QA
      to: Done
      name: "Pass QA"
      post_functions:
        - resolve_issue

Best Practices

  1. Keep Issues Small: Break down to complete in 1-2 days
  2. Write Clear Descriptions: Include all context needed
  3. Link Related Issues: Use proper issue linking
  4. Update Status Regularly: Move cards as work progresses
  5. Use Labels Consistently: Establish team conventions
  6. Estimate in Points: Use relative sizing
  7. Review Backlog Weekly: Keep backlog groomed

Frequently asked questions

What does the Jira Automation AI skill do?

Automate Jira project management workflows, sprint planning, issue tracking, and reporting

Why use Jira Automation on TypingMind?

Because you install it once and use it with any model. Jira Automation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Jira Automation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/claude-office-skills/skills/tree/main/jira-automation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Jira Automation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Jira Automation?

As many as you like. As long as a model supports skills, you can use Jira Automation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Jira Automation AI skill free?

Yes. It is published on GitHub by claude-office-skills under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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