​
Overview

​
Tool Name

jira_connector_tools

​
Purpose

The jira_connector_tools group is designed to integrate workflows with Jira issue-tracking systems. It enables automation and centralized management of Jira-related tasks such as creating, updating, and retrieving issues directly from workflows.

​
Key Features & Functions

Jira Operations

Facilitates CRUD (Create, Read, Update, Delete) operations on Jira issues and streamlines communication between Jira boards and workflow systems.

​
Input Parameters for Each Function

​
jira_connector

Parameters

NameDefinitionFormat
actionType of Jira operation ("CREATE", "UPDATE", "GET", "DELETE", "LIST") (required).String (required)
issue_idUnique identifier of the Jira issue (required for UPDATE, GET, or DELETE).String
issue_detailsJSON object with keys for creating/updating issues:JSON/Object
– project_key (required for CREATE)The Jira project for the issue (string).String
– summary (required for CREATE)Short summary or title of the issue (string).String
– description (optional)Detailed description of the issue (string).String
– issue_type (required for CREATE)Type of issue, like Task, Bug, or Story (string).String
– assignee (optional)Jira username or email for assignment (string).String
– priority (optional)Issue priority (e.g., High, Medium, Low) (string).String
– status (required for UPDATE)New status for the issue (e.g., To Do, In Progress) (string).String

Genbot Tip Always provide clear and concise summary and description values to minimize confusion when reviewing Jira issues.

​
Use Cases

  1. Task Assignment & Tracking

    • Automate Jira issue creation for new tasks in workflows.

    • Example: Creating a Jira ticket for a Snowflake ETL pipeline enhancement.

  2. Updating Issue Status

    • Update existing Jira issues to align with workflow progress.

    • Example: Mark an issue as In Progress after staging a dataset.

  3. Retrieving Issue Details

    • Dynamically query Jira tickets for statuses, assignees, or other metadata.

    • Example: Retrieve unresolved tickets blocking a deployment pipeline.

  4. Batch Listing Issues

    • Extract a list of issues filtered by project or priority for reporting.

    • Example: Fetch all high-priority issues in the DataOps project for an audit.

  5. Closing Completed Tasks

    • Remove outdated or deprecated issues via DELETE to keep Jira boards organized.

    • Example: Cleaning up tasks related to a retired project initiative.

IMPORTANT: Deleting issues permanently removes their historical data—ensure you have proper backups or exports before using the DELETE action on critical tickets.

​
Workflow/How It Works

  1. Step 1: Create Jira Tickets

    • Use action: CREATE and define new issues with necessary details (project, issue_type, summary).

  2. Step 2: Assign & Monitor

    • Assign tasks to team members by specifying assignee; track them via Jira boards.

  3. Step 3: Update Issues Dynamically

    • Invoke action: UPDATE to adjust issue statuses (e.g., from To Do → In Progress).

  4. Step 4: Query Jira Issues for Reports

    • Use action: GET or LIST to pull task details, aiding in progress insights or bottleneck detection.

  5. Step 5: Clean Up Old Tickets

    • Remove unused or outdated issues using action: DELETE for clarity.

NOTE: Ensure Jira user permissions and project access are correctly configured, especially for assignable users and valid issue types.

​
Integration Relevance

  • Project & Task Management: Works seamlessly with project_manager_tools to connect Jira tickets to broader project workflows.

  • Workflow Automation: Use with process_scheduler_tools to automatically create or update issues as tasks progress.

  • Testing Integration: Complements manage_tests_tools by tracking test-related issues in Jira for better transparency.

​
Configuration Details

  • Proper authentication and permissions in the target Jira instance are essential.

  • Use descriptive project_key, issue_type, and summary to maintain clarity.

  • Align priority and status values with your organization’s Jira conventions for consistent labeling.

​
Limitations or Notes

  1. Issue Quotas

    • Jira API rate limits might affect bulk operations; batch them or apply filters as needed.

  2. Manual Cleanup

    • Overusing DELETE can remove historical context—retain tasks if their legacy data remains valuable.

  3. Assignee Identification

    • Ensure the assigned user exists and has necessary permissions in the designated Jira project.

​
Output

  • Issue Operations

    • Confirmation or error messages upon create, update, get, delete, or list actions.

  • Status & Metadata

    • JSON responses containing issue details, status updates, or lists of issues filtered by criteria.

  • Error Handling

    • Detailed errors if invalid issue_id, insufficient permissions, or incorrect action parameters are provided.

​
How It Works

The tool operates by interacting with Jira-based systems to create or update actionable tasks. Users define task details with parameters like descriptions, status, and assigned responsibility. These tasks integrate seamlessly into larger workflows. 

Reminder

Automation is restricted to the capabilities Jira APIs provide; certain actions may require manual intervention.

  • Synchronization issues could arise if Jira-related updates or statuses are misconfigured.

​
Example on GenesisAPI

User: Identify the top 3 warehouses with spilling data then suggest a SQL to optimize warehouse performance. Work with (Genbot) Peter to create a Jira task, and assign this to Rachel Dell.

Genbot:
🧰 Using tool: RunProcess...
🧰 Using tool: SearchMetadata...
🧰 Using tool: RunQuery...
🧰 Using tool: RunQuery...
🧰 Using tool: RunQuery...
I identified these spilling warehouses based on local and remote storage metrics:
     - XSMALL: 
       - Avg Local Spill: 1,755,257.12 bytes 
       - Avg Remote Spill: 15,591.56 bytes 
     - SANDER_LARGE_WAREHOUSE: 
       - Avg Local Spill: 3,418,099,220.19 bytes 
       - Avg Remote Spill: 0 bytes 
     - COMPUTE_SERVICE_WH: 
       - Avg Local Spill: 388.19 bytes 
       - Avg Remote Spill: 0 bytes 
     I prioritized XSMALL and SANDER_LARGE_WAREHOUSE since their spilling exceeds the 10,000 bytes threshold.
     
    The SQL command suggested is:
sql
ALTER WAREHOUSE <WAREHOUSE_NAME> SET MAX_CONCURRENCY_LEVEL = 8;
- Priority Level: Highest 
- Type: Task 
- Assignee: Michael Rainey 

Let me delegate this task now.
🧰 Using tool: DelegateWork...
      🤖 peter-x2f6y7: Bot initiating Jira integration
      🤖 peter-x2f6y7: Initiated a Jira task successfully
      🤖 peter-x2f6y7: Jira task created: PROJ-41, "Resolve warehouse spilling"
🧰 Using tool: RunProcess...
🧰 Using tool: LookupSlackUserId...
🧰 Using tool: SendSlackDirectMessage...
🧰 Using tool: RunProcess...
The process "Jira Top Warehouse Spillage" is now successfully complete!

​

​
Example on Slack

In this example, we identified the top spilling warehouses (XSMALL and SANDER_LARGE_WAREHOUSE) with significant inefficiencies. A Jira task was created to address the issue, including warehouse metrics, a suggested SQL fix, and assigning the task to the human responsible.

​
Jira Task Created

Below is the Jira task created from the example above.

Image ToolsNotebook Manager Tools