Jira Workflow logo

Jira Workflow

Organization
aiskillstore
jira-workflow

Orchestrate Jira workflows end-to-end. Use when building stories with approvals, transitioning items through lifecycle states, or syncing task completion with Jira.

Overview

Publisheraiskillstore
Repositorymarketplace
Skill namejira-workflow
Stars
427
Forks
45
Bundled files
Instructions only
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 aiskillstore on GitHub. Read the source before you install it.

Installation

Install the Jira Workflow 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.
  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/aiskillstore/marketplace.git /tmp/marketplace
mkdir -p .claude/skills
cp -r /tmp/marketplace/skills/01000001-01001110/jira-safe/jira-workflow .claude/skills/jira-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jira Workflow 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 Workflow 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 Workflow 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 Workflow Orchestration Skill

Complete workflow management for Jira: building stories (SAFe), getting approvals, and transitioning items through the development lifecycle (To Do → Progressing → Done).

IMPORTANT: This project uses Next-Gen (Team-managed) Jira with custom workflow states. The actual states are:

  • To Do (backlog)
  • In Review
  • Progressing (active work)
  • Out Review
  • Done

Always query available transitions first: GET /rest/api/3/issue/{key}/transitions

When to Use

  • Creating new user stories, epics, or tasks for the project
  • Getting user approval before creating Jira items
  • Moving stories through workflow states as work progresses
  • Syncing Claude Code task completion with Jira status
  • Managing sprint planning and backlog refinement
  • Tracking development progress in real-time

Prerequisites

Environment Variables:

bash
JIRA_EMAIL=your.email@domain.com
JIRA_API_TOKEN=your_api_token
JIRA_BASE_URL=https://your-org.atlassian.net
JIRA_PROJECT_KEY=SCRUM
JIRA_BOARD_ID=1

Project Configuration:

  • Must know if project is Next-Gen (Team-managed) or Classic (Company-managed)
  • Next-Gen: Use parent field for Epic links
  • Classic: Use customfield_10014 for Epic links

Core Workflow Pattern

The Approval-Create-Track Loop

1. PLAN: Analyze task requirements
2. PROPOSE: Present story to user for approval
3. APPROVE: User confirms or modifies
4. CREATE: Issue created in Jira backlog
5. START: Transition to "Progressing" when work begins
6. COMPLETE: Transition to "Done" when work verified
7. SYNC: Update Jira with implementation details

Phase 1: Story Building (SAFe Format)

Building a Story Proposal

When user requests work, build a SAFe-compliant story proposal:

javascript
function buildStoryProposal(task) {
  return {
    summary: `As a ${task.persona}, I want ${task.goal}, so that ${task.benefit}`,
    description: {
      userStory: `As a **${task.persona}**, I want **${task.goal}**, so that **${task.benefit}**.`,
      acceptanceCriteria: task.scenarios.map(s => ({
        name: s.name,
        given: s.given,
        when: s.when,
        then: s.then
      })),
      definitionOfDone: [
        'Code reviewed and approved',
        'Unit tests written and passing',
        'Integration tests passing',
        'Documentation updated',
        'Deployed to staging',
        'Validated in production'
      ],
      technicalNotes: task.technicalNotes || []
    },
    category: task.category, // authentication, ui, api, database, etc.
    estimatedComplexity: task.complexity || 'medium', // small, medium, large
    subtasks: task.subtasks || []
  };
}

Presenting for Approval

CRITICAL: Always get user approval before creating Jira items.

Use this prompt pattern:

markdown
## Proposed Jira Story

**Summary:** As a [persona], I want [goal], so that [benefit]

**Category:** [category]
**Complexity:** [small/medium/large]

### Acceptance Criteria

**Scenario 1: [Name]**
- **GIVEN** [precondition]
- **WHEN** [action]
- **THEN** [expected result]

### Subtasks (if any)
1. [Subtask 1]
2. [Subtask 2]
3. [Subtask 3]

---

**Do you want me to create this in Jira?**

Options:
1. **Yes, create as-is** - I'll create the story now
2. **Modify** - Tell me what to change
3. **Skip** - Don't create in Jira, just do the work

Phase 2: Issue Creation

Create Story in Jira

javascript
const JIRA_EMAIL = process.env.JIRA_EMAIL;
const JIRA_API_TOKEN = process.env.JIRA_API_TOKEN;
const JIRA_BASE_URL = process.env.JIRA_BASE_URL;
const PROJECT_KEY = process.env.JIRA_PROJECT_KEY;

const auth = Buffer.from(`${JIRA_EMAIL}:${JIRA_API_TOKEN}`).toString('base64');
const headers = {
  'Authorization': `Basic ${auth}`,
  'Content-Type': 'application/json',
  'Accept': 'application/json'
};

async function createStory(proposal, epicKey = null) {
  const body = {
    fields: {
      project: { key: PROJECT_KEY },
      issuetype: { name: 'Story' },
      summary: proposal.summary,
      description: buildADF(proposal.description),
      labels: [proposal.category.toLowerCase().replace(/\s+/g, '-')]
    }
  };

  // Link to Epic (Next-Gen project)
  if (epicKey) {
    body.fields.parent = { key: epicKey };
  }

  const response = await fetch(`${JIRA_BASE_URL}/rest/api/3/issue`, {
    method: 'POST',
    headers,
    body: JSON.stringify(body)
  });

  if (!response.ok) {
    const error = await response.text();
    throw new Error(`Failed to create story: ${error}`);
  }

  const issue = await response.json();
  console.log(`Created: ${issue.key} - ${proposal.summary}`);

  // Create subtasks if any
  if (proposal.subtasks?.length > 0) {
    for (const subtask of proposal.subtasks) {
      await createSubtask(issue.key, subtask);
      await delay(100); // Rate limiting
    }
  }

  return issue;
}

async function createSubtask(parentKey, summary) {
  const body = {
    fields: {
      project: { key: PROJECT_KEY },
      issuetype: { name: 'Subtask' }, // Note: 'Subtask' for Next-Gen
      parent: { key: parentKey },
      summary: summary
    }
  };

  const response = await fetch(`${JIRA_BASE_URL}/rest/api/3/issue`, {
    method: 'POST',
    headers,
    body: JSON.stringify(body)
  });

  if (!response.ok) {
    const error = await response.text();
    throw new Error(`Failed to create subtask: ${error}`);
  }

  return response.json();
}

function delay(ms) {
  return new Promise(resolve => setTimeout(resolve, ms));
}

Build Atlassian Document Format (ADF)

javascript
function buildADF(content) {
  const sections = [];

  // User Story Section
  sections.push({
    type: 'heading',
    attrs: { level: 2 },
    content: [{ type: 'text', text: 'User Story' }]
  });
  sections.push({
    type: 'paragraph',
    content: [{ type: 'text', text: content.userStory }]
  });

  // Acceptance Criteria Section
  sections.push({
    type: 'heading',
    attrs: { level: 2 },
    content: [{ type: 'text', text: 'Acceptance Criteria' }]
  });

  for (const scenario of content.acceptanceCriteria) {
    sections.push({
      type: 'heading',
      attrs: { level: 3 },
      content: [{ type: 'text', text: `Scenario: ${scenario.name}` }]
    });
    sections.push({
      type: 'bulletList',
      content: [
        { type: 'listItem', content: [{ type: 'paragraph', content: [{ type: 'text', text: `GIVEN ${scenario.given}`, marks: [{ type: 'strong' }] }] }] },
        { type: 'listItem', content: [{ type: 'paragraph', content: [{ type: 'text', text: `WHEN ${scenario.when}`, marks: [{ type: 'strong' }] }] }] },
        { type: 'listItem', content: [{ type: 'paragraph', content: [{ type: 'text', text: `THEN ${scenario.then}`, marks: [{ type: 'strong' }] }] }] }
      ]
    });
  }

  // Definition of Done Section
  sections.push({
    type: 'heading',
    attrs: { level: 2 },
    content: [{ type: 'text', text: 'Definition of Done' }]
  });
  sections.push({
    type: 'bulletList',
    content: content.definitionOfDone.map(item => ({
      type: 'listItem',
      content: [{ type: 'paragraph', content: [{ type: 'text', text: `[ ] ${item}` }] }]
    }))
  });

  // Technical Notes (if any)
  if (content.technicalNotes?.length > 0) {
    sections.push({
      type: 'heading',
      attrs: { level: 2 },
      content: [{ type: 'text', text: 'Technical Notes' }]
    });
    sections.push({
      type: 'bulletList',
      content: content.technicalNotes.map(note => ({
        type: 'listItem',
        content: [{ type: 'paragraph', content: [{ type: 'text', text: note }] }]
      }))
    });
  }

  return { type: 'doc', version: 1, content: sections };
}

Phase 3: Workflow Transitions

Get Available Transitions

javascript
async function getTransitions(issueKey) {
  const response = await fetch(
    `${JIRA_BASE_URL}/rest/api/3/issue/${issueKey}/transitions`,
    { headers }
  );

  if (!response.ok) {
    throw new Error(`Failed to get transitions: ${response.status}`);
  }

  const data = await response.json();
  return data.transitions;
}

Transition Issue to State

javascript
async function transitionTo(issueKey, targetState) {
  // Get available transitions
  const transitions = await getTransitions(issueKey);

  // Find the transition to target state
  const transition = transitions.find(t =>
    t.to.name.toLowerCase() === targetState.toLowerCase() ||
    t.name.toLowerCase() === targetState.toLowerCase()
  );

  if (!transition) {
    console.log(`Available transitions for ${issueKey}:`);
    transitions.forEach(t => console.log(`  - ${t.name}${t.to.name}`));
    throw new Error(`No transition to "${targetState}" found`);
  }

  // Execute the transition
  const response = await fetch(
    `${JIRA_BASE_URL}/rest/api/3/issue/${issueKey}/transitions`,
    {
      method: 'POST',
      headers,
      body: JSON.stringify({ transition: { id: transition.id } })
    }
  );

  if (!response.ok) {
    const error = await response.text();
    throw new Error(`Failed to transition: ${error}`);
  }

  console.log(`${issueKey} transitioned to ${targetState}`);
  return true;
}

Common Workflow Operations

javascript
// Start work on a story (To Do → Progressing)
async function startWork(issueKey) {
  await transitionTo(issueKey, 'Progressing');
  console.log(`Started: ${issueKey}`);
}

// Complete a story (Progressing → Done)
async function completeWork(issueKey) {
  await transitionTo(issueKey, 'Done');
  console.log(`Completed: ${issueKey}`);
}

// Move back to backlog (any state → To Do)
async function moveToBacklog(issueKey) {
  await transitionTo(issueKey, 'To Do');
  console.log(`Moved to backlog: ${issueKey}`);
}

// Reopen a completed issue (Done → To Do)
async function reopenWork(issueKey) {
  await transitionTo(issueKey, 'To Do');
  console.log(`Reopened: ${issueKey}`);
}

Phase 4: Add Comments and Updates

Add Work Log Comment

javascript
async function addComment(issueKey, comment) {
  const body = {
    body: {
      type: 'doc',
      version: 1,
      content: [
        {
          type: 'paragraph',
          content: [{ type: 'text', text: comment }]
        }
      ]
    }
  };

  const response = await fetch(
    `${JIRA_BASE_URL}/rest/api/3/issue/${issueKey}/comment`,
    {
      method: 'POST',
      headers,
      body: JSON.stringify(body)
    }
  );

  if (!response.ok) {
    throw new Error(`Failed to add comment: ${response.status}`);
  }

  console.log(`Comment added to ${issueKey}`);
  return response.json();
}

Add Implementation Details Comment

javascript
async function addImplementationDetails(issueKey, details) {
  const content = [
    { type: 'heading', attrs: { level: 3 }, content: [{ type: 'text', text: 'Implementation Details' }] },
    { type: 'paragraph', content: [{ type: 'text', text: `Completed: ${new Date().toISOString()}` }] }
  ];

  if (details.files?.length > 0) {
    content.push(
      { type: 'heading', attrs: { level: 4 }, content: [{ type: 'text', text: 'Files Modified' }] },
      {
        type: 'bulletList',
        content: details.files.map(f => ({
          type: 'listItem',
          content: [{ type: 'paragraph', content: [{ type: 'text', text: f }] }]
        }))
      }
    );
  }

  if (details.commits?.length > 0) {
    content.push(
      { type: 'heading', attrs: { level: 4 }, content: [{ type: 'text', text: 'Commits' }] },
      {
        type: 'bulletList',
        content: details.commits.map(c => ({
          type: 'listItem',
          content: [{ type: 'paragraph', content: [{ type: 'text', text: c }] }]
        }))
      }
    );
  }

  if (details.notes) {
    content.push(
      { type: 'heading', attrs: { level: 4 }, content: [{ type: 'text', text: 'Notes' }] },
      { type: 'paragraph', content: [{ type: 'text', text: details.notes }] }
    );
  }

  const body = { body: { type: 'doc', version: 1, content } };

  const response = await fetch(
    `${JIRA_BASE_URL}/rest/api/3/issue/${issueKey}/comment`,
    {
      method: 'POST',
      headers,
      body: JSON.stringify(body)
    }
  );

  return response.json();
}

Complete Workflow Example

Full Cycle: Propose → Approve → Create → Work → Complete

javascript
async function fullWorkflowCycle(task) {
  // 1. Build proposal
  const proposal = buildStoryProposal(task);

  // 2. Present for approval (use AskUserQuestion tool)
  const approved = await presentForApproval(proposal);

  if (!approved) {
    console.log('Story creation skipped by user');
    return null;
  }

  // 3. Create in Jira
  const issue = await createStory(proposal, task.epicKey);
  console.log(`Created: ${issue.key}`);

  // 4. Start work (transition to In Progress)
  await startWork(issue.key);

  // 5. Do the actual work (your implementation here)
  const result = await doTheWork(task);

  // 6. Add implementation details
  await addImplementationDetails(issue.key, {
    files: result.modifiedFiles,
    commits: result.commits,
    notes: result.notes
  });

  // 7. Complete the work
  await completeWork(issue.key);

  return issue;
}

Integration with Claude Code Orchestration

Sync with TodoWrite

When working on Jira stories, sync with TodoWrite:

markdown
TodoWrite todos:
[
  { "content": "SCRUM-55: Create signup API", "status": "in_progress", "activeForm": "Working on SCRUM-55" },
  { "content": "SCRUM-56: Create login API", "status": "pending", "activeForm": "Waiting for SCRUM-55" },
  { "content": "SCRUM-57: Create logout API", "status": "pending", "activeForm": "Waiting for SCRUM-56" }
]

As each task completes:
1. Mark TodoWrite item as completed
2. Transition Jira issue to Done
3. Add implementation comment to Jira
4. Move to next task

Auto-Transition Pattern

javascript
// When starting a task
async function startTask(issueKey) {
  // 1. Transition Jira to Progressing
  await startWork(issueKey);

  // 2. Update TodoWrite (in Claude Code)
  // TodoWrite: Mark as in_progress

  return issueKey;
}

// When completing a task
async function completeTask(issueKey, details) {
  // 1. Add implementation comment
  await addImplementationDetails(issueKey, details);

  // 2. Transition Jira to Done
  await completeWork(issueKey);

  // 3. Update TodoWrite (in Claude Code)
  // TodoWrite: Mark as completed

  return issueKey;
}

Quick Reference

Status Transitions (SCRUM Project - Next-Gen)

FromToTransition NameTypical Use
To DoProgressing"Progressing"Starting work
To DoIn Review"In Review"Needs review first
ProgressingDone"Done"Work complete
ProgressingTo Do"To Do"Blocked/deprioritized
DoneTo Do"To Do"Reopening

Available States: To Do, In Review, Progressing, Out Review, Done

Note: Always query transitions first - they vary by issue type and current state.

API Endpoints

ActionMethodEndpoint
Create IssuePOST/rest/api/3/issue
Get IssueGET/rest/api/3/issue/{key}
Update IssuePUT/rest/api/3/issue/{key}
Delete IssueDELETE/rest/api/3/issue/{key}
Get TransitionsGET/rest/api/3/issue/{key}/transitions
Do TransitionPOST/rest/api/3/issue/{key}/transitions
Add CommentPOST/rest/api/3/issue/{key}/comment
SearchGET/rest/api/3/search/jql?jql=...

Rate Limiting

  • Max 10 requests/second
  • Add 100ms delay between bulk operations
  • Batch operations where possible

Error Handling

javascript
async function safeJiraOperation(operation, issueKey) {
  try {
    return await operation();
  } catch (error) {
    console.error(`Jira operation failed for ${issueKey}: ${error.message}`);

    // Common error patterns
    if (error.message.includes('404')) {
      console.log('Issue not found - may have been deleted');
    }
    if (error.message.includes('401')) {
      console.log('Authentication failed - check API token');
    }
    if (error.message.includes('403')) {
      console.log('Permission denied - check project access');
    }
    if (error.message.includes('400')) {
      console.log('Bad request - check field names and values');
    }

    throw error;
  }
}

Executable Scripts

Ready-to-run scripts are available in both Node.js and Python:

Using the Cross-Platform Runner

bash
# From the .claude/skills/jira directory
node scripts/run.js workflow demo SCRUM-100  # Demo full workflow
node scripts/run.js test                      # Test authentication

# Force specific runtime
node scripts/run.js --python workflow demo SCRUM-100
node scripts/run.js --node workflow demo SCRUM-100

Direct Script Execution

bash
# Node.js
node scripts/jira-workflow-demo.mjs demo SCRUM-100
node scripts/jira-workflow-demo.mjs start SCRUM-100
node scripts/jira-workflow-demo.mjs complete SCRUM-100
node scripts/jira-workflow-demo.mjs reopen SCRUM-100
node scripts/jira-workflow-demo.mjs status SCRUM-100

# Python (recommended on Windows)
python scripts/jira-workflow-demo.py demo SCRUM-100
python scripts/jira-workflow-demo.py start SCRUM-100
python scripts/jira-workflow-demo.py complete SCRUM-100
python scripts/jira-workflow-demo.py reopen SCRUM-100
python scripts/jira-workflow-demo.py status SCRUM-100

Available Scripts

ScriptNode.jsPythonPurpose
Workflow Demojira-workflow-demo.mjsjira-workflow-demo.pyFull To Do → Progressing → Done demo
Add Subtasksjira-add-subtasks.mjsjira-add-subtasks.pyCreate subtasks under a story
Create Storyjira-create-one.mjsjira-create-one.pyCreate single story
Bulk Createjira-bulk-create.mjsjira-bulk-create.pyCreate from git commits

References

Frequently asked questions

What does the Jira Workflow AI skill do?

Orchestrate Jira workflows end-to-end. Use when building stories with approvals, transitioning items through lifecycle states, or syncing task completion with Jira.

Why use Jira Workflow on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aiskillstore/marketplace/tree/main/skills/01000001-01001110/jira-safe/jira-workflow. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Jira Workflow?

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 Workflow?

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

Is the Jira Workflow AI skill free?

It is published on GitHub by aiskillstore. Check the repository for licensing terms. 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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