Jira Task logo

Jira Task

Organization
Gentleman-Programming
jira-task

Creates Jira tasks following Prowler's standard format. Trigger: When user asks to create a Jira task, ticket, or issue.

Overview

PublisherGentleman-Programming
RepositoryGentleman-Skills
Skill namejira-task
Stars
658
Forks
98
Bundled files
Instructions only
LicenseApache-2.0
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 Gentleman-Programming on GitHub. Read the source before you install it.

Installation

Install the Jira Task 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/Gentleman-Programming/Gentleman-Skills/tree/main/curated/jira-task
  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/Gentleman-Programming/Gentleman-Skills.git /tmp/Gentleman-Skills
mkdir -p .claude/skills
cp -r /tmp/Gentleman-Skills/curated/jira-task .claude/skills/jira-task
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jira Task 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 Task 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 Task 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.

When to Use

Use this skill when creating Jira tasks for:

  • Bug reports
  • Feature requests
  • Refactoring tasks
  • Documentation tasks

Multi-Component Work: Split into Multiple Tasks

IMPORTANT: When work requires changes in multiple components (API, UI, SDK), create separate tasks for each component instead of one big task.

Why Split?

  • Different developers can work in parallel
  • Easier to review and test
  • Better tracking of progress
  • API needs to be done before UI (dependency)

Bug vs Feature: Different Structures

For BUGS: Create separate sibling tasks

Bugs are typically urgent fixes, so create independent tasks per component:

Task 1 - API:

  • Title: [BUG] Add aws_region field to AWS provider secrets (API)
  • Must be done first (UI depends on it)

Task 2 - UI:

  • Title: [BUG] Add region selector to AWS provider connection form (UI)
  • Blocked by API task
For FEATURES: Create parent + child tasks

Features need business context for stakeholders, so use a parent-child structure:

Parent Task (for PM/Stakeholders):

  • Title: [FEATURE] AWS GovCloud support
  • Contains: Feature overview, user story, acceptance criteria from USER perspective
  • NO technical details
  • Links to child tasks

Child Task 1 - API:

  • Title: [FEATURE] AWS GovCloud support (API)
  • Contains: Technical details, affected files, API-specific acceptance criteria
  • Links to parent

Child Task 2 - UI:

  • Title: [FEATURE] AWS GovCloud support (UI)
  • Contains: Technical details, component paths, UI-specific acceptance criteria
  • Links to parent, blocked by API task

Parent Task Template (Features Only)

markdown
## Description

{User-facing description of the feature - what problem does it solve?}

## User Story

As a {user type}, I want to {action} so that {benefit}.

## Acceptance Criteria (User Perspective)

- [ ] User can {do something}
- [ ] User sees {something}
- [ ] {Behavior from user's point of view}

## Out of Scope

- {What this feature does NOT include}

## Design

- Figma: {link if available}
- Screenshots/mockups if available

## Child Tasks

- [ ] `[FEATURE] {Feature name} (API)` - Backend implementation
- [ ] `[FEATURE] {Feature name} (UI)` - Frontend implementation

## Priority

{High/Medium/Low} ({business justification})

Child Task Template (Features Only)

markdown
## Description

Technical implementation of {feature name} for {component}.

## Parent Task

`[FEATURE] {Feature name}`

## Acceptance Criteria (Technical)

- [ ] {Technical requirement 1}
- [ ] {Technical requirement 2}

## Technical Notes

- Affected files:
  - `{file path 1}`
  - `{file path 2}`
- {Implementation hints}

## Testing

- [ ] {Test case 1}
- [ ] {Test case 2}

## Related Tasks

- Parent: `[FEATURE] {Feature name}`
- Blocked by: {if any}
- Blocks: {if any}

Linking Tasks

In each task description, add:

markdown
## Related Tasks
- Parent: [Parent task title/link] (for child tasks)
- Blocked by: [API task title/link]
- Blocks: [UI task title/link]

Task Template

markdown
## Description

{Brief explanation of the problem or feature request}

**Current State:**
- {What's happening now / What's broken}
- {Impact on users}

**Expected State:**
- {What should happen}
- {Desired behavior}

## Acceptance Criteria

- [ ] {Specific, testable requirement}
- [ ] {Another requirement}
- [ ] {Include both API and UI tasks if applicable}

## Technical Notes

- {Implementation hints}
- {Affected files with full paths}
- {Dependencies or related components}

## Testing

- [ ] {Test case 1}
- [ ] {Test case 2}
- [ ] {Include regression tests}

## Priority

{High/Medium/Low} ({justification})

Title Conventions

Format: [TYPE] Brief description (components)

Types:

  • [BUG] - Something broken that worked before
  • [FEATURE] - New functionality
  • [ENHANCEMENT] - Improvement to existing feature
  • [REFACTOR] - Code restructure without behavior change
  • [DOCS] - Documentation only
  • [CHORE] - Maintenance, dependencies, CI/CD

Components (when multiple affected):

  • (API) - Backend only
  • (UI) - Frontend only
  • (SDK) - Prowler SDK only
  • (API + UI) - Both backend and frontend
  • (SDK + API) - SDK and backend
  • (Full Stack) - All components

Examples:

  • [BUG] AWS GovCloud accounts cannot connect - STS region hardcoded (API + UI)
  • [FEATURE] Add dark mode toggle (UI)
  • [REFACTOR] Migrate E2E tests to Page Object Model (UI)
  • [ENHANCEMENT] Improve scan performance for large accounts (SDK)

Priority Guidelines

PriorityCriteria
CriticalProduction down, data loss, security vulnerability
HighBlocks users, no workaround, affects paid features
MediumHas workaround, affects subset of users
LowNice to have, cosmetic, internal tooling

Affected Files Section

Always include full paths when known:

markdown
## Technical Notes

- Affected files:
  - `api/src/backend/api/v1/serializers.py`
  - `ui/components/providers/workflow/forms/aws-credentials-form.tsx`
  - `prowler/providers/aws/config.py`

Component-Specific Sections

API Tasks

Include:

  • Serializer changes
  • View/ViewSet changes
  • Migration requirements
  • API spec regeneration needs

UI Tasks

Include:

  • Component paths
  • Form validation changes
  • State management impact
  • Responsive design considerations

SDK Tasks

Include:

  • Provider affected
  • Service affected
  • Check changes
  • Config changes

Checklist Before Submitting

  1. ✅ Title follows [TYPE] description (components) format
  2. ✅ Description has Current/Expected State
  3. ✅ Acceptance Criteria are specific and testable
  4. ✅ Technical Notes include file paths
  5. ✅ Testing section covers happy path + edge cases
  6. ✅ Priority has justification
  7. ✅ Multi-component work is split into separate tasks
  8. ✅ Titles are recommended for all tasks

Output Format

For BUGS (sibling tasks):

markdown
## Recommended Tasks

### Task 1: [BUG] {Description} (API)
{Full task content}

---

### Task 2: [BUG] {Description} (UI)
{Full task content}

For FEATURES (parent + children):

markdown
## Recommended Tasks

### Parent Task: [FEATURE] {Feature name}
{User-facing content, no technical details}

---

### Child Task 1: [FEATURE] {Feature name} (API)
{Technical content for API team}

---

### Child Task 2: [FEATURE] {Feature name} (UI)
{Technical content for UI team}

Formatting Rules

CRITICAL: All output MUST be in Markdown format, ready to paste into Jira.

  • Use ## for main sections (Description, Acceptance Criteria, etc.)
  • Use **bold** for emphasis
  • Use - [ ] for checkboxes
  • Use ``` for code blocks with language hints
  • Use backticks for file paths, commands, and code references
  • Use tables where appropriate
  • Use --- to separate multiple tasks

Jira MCP Integration

CRITICAL: When creating tasks via MCP, use these exact parameters:

Required Fields

json
{
  "project_key": "PROWLER",
  "summary": "[TYPE] Task title (component)",
  "issue_type": "Task",
  "additional_fields": {
    "parent": "PROWLER-XXX",
    "customfield_10359": {"value": "UI"}
  }
}

Team Field (REQUIRED)

The customfield_10359 (Team) field is REQUIRED. Options:

  • "UI" - Frontend tasks
  • "API" - Backend tasks
  • "SDK" - Prowler SDK tasks

Work Item Description Field

IMPORTANT: The project uses customfield_10363 (Work Item Description) instead of the standard description field for display in the UI.

CRITICAL: Use Jira Wiki markup, NOT Markdown:

  • h2. instead of ##
  • *text* for bold instead of **text**
  • * item for bullets (same)
  • ** subitem for nested bullets

After creating the issue, update the description with:

json
{
  "customfield_10363": "h2. Description\n\n{content}\n\n*Current State:*\n* {problem 1}\n* {problem 2}\n\n*Expected State:*\n* {solution 1}\n* {solution 2}\n\nh2. Acceptance Criteria\n\n* {criteria 1}\n* {criteria 2}\n\nh2. Technical Notes\n\nPR: [{pr_url}]\n\nAffected files:\n* {file 1}\n* {file 2}\n\nh2. Testing\n\n* [ ] PR - Local environment\n** {test case 1}\n** {test case 2}\n* [ ] After merge in prowler - dev\n** {test case 3}"
}

Common Epics

EpicKeyUse For
UI - Bugs & ImprovementsPROWLER-193UI bugs, enhancements
API - Bugs / ImprovementsPROWLER-XXXAPI bugs, enhancements
LightHouse AIPROWLER-594AI features
Technical Debt - UIPROWLER-502Refactoring

Workflow Transitions

Backlog (10037) → To Do (14) → In Progress (11) → Done (21)
                → Blocked (10)

MCP Commands Sequence

  1. Create issue:
mcp__mcp-atlassian__jira_create_issue
  1. Update Work Item Description:
mcp__mcp-atlassian__jira_update_issue with customfield_10363
  1. Assign and transition:
mcp__mcp-atlassian__jira_update_issue (assignee)
mcp__mcp-atlassian__jira_transition_issue (status)

Keywords

jira, task, ticket, issue, bug, feature, prowler

Frequently asked questions

What does the Jira Task AI skill do?

Creates Jira tasks following Prowler's standard format. Trigger: When user asks to create a Jira task, ticket, or issue.

Why use Jira Task on TypingMind?

Because you install it once and use it with any model. Jira Task 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 Task in TypingMind?

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

Which AI models can use Jira Task?

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 Task?

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

Is the Jira Task AI skill free?

Yes. It is published on GitHub by Gentleman-Programming under the Apache-2.0 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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