FAQ

What is JQL and how do I write a query?

JQL (Jira Query Language) is Jira's search syntax. It lets you filter issues by any field. Common examples:

• project = "PROJ" — Issues in a specific project

• status = "Done" — Completed issues

• assignee = currentUser() — Issues assigned to you

• created >= -7d — Issues created in the last 7 days

• priority = "High" AND type = "Bug" — High-priority bugs

See Atlassian's JQL tutorial for detailed documentation.

Can I use macros in my JQL query?

Yes! Coupler.io supports Jira macros like currentUser(), now(), and relative dates (-7d, -30d, -1h). This is useful for queries that need to be dynamic:

• assignee = currentUser() — Always pulls issues for the logged-in user

• updated >= -1d — Issues updated in the last day

• created >= startOfMonth() — Issues created since the first of the month

Learn more about macros in Coupler.io.

What's the difference between "Jira CSV export" and "Detailed data" formats?

Jira CSV export uses Jira's standard export format with commonly-used fields (Summary, Status, Assignee, etc.). It's simpler and more readable.

Detailed data exports all metadata including issue IDs, URLs, and raw API values. It's better if you're joining Jira data with other sources or doing advanced analysis in BigQuery. User fields (Assignee, Reporter) will show account IDs instead of names in this format.

Choose based on your destination: use CSV export for Google Sheets dashboards, detailed data for warehouse analysis.

Can I pull data from multiple Jira projects in one data flow?

Yes! Use JQL to query multiple projects: project in ("PROJ1", "PROJ2", "PROJ3"). This pulls all issues from all three projects into a single list. You can then filter or group them in your destination (Google Sheets, BigQuery, etc.).

If you need to keep projects separate or apply different transformations to each, create multiple data flows—one per project.

How do I export only specific columns?

Enter column names (one per line) in the "Columns" field. To find exact column names, export a sample of your data first and copy the header row.

If you leave "Columns" blank, all navigable fields will be exported. Limiting columns can speed up your data flow, especially if your Jira instance has many custom fields.

Can I join Jira data with other sources?

Yes! Coupler.io supports Join, Append, and Aggregate transformations. For example:

• Join Jira issues with your time-tracking system on issue key

• Append issues from multiple Jira projects into one dataset

• Aggregate story points by assignee to see workload distribution

Use the "Detailed data" export format to preserve IDs and metadata for cleaner joins.

See the data overview for common metric combinations and analysis patterns.

Can I send Jira data to an AI destination like Claude or ChatGPT?

Yes! Coupler.io supports AI destinations including Claude, ChatGPT, Cursor, Gemini, Perplexity, and OpenClaw. You can export Jira issues directly to these platforms for analysis, summarization, or other AI-powered tasks. Select your preferred AI destination when setting up the data flow.

Why is my data flow running slowly on large exports?

Jira Cloud API has rate limits (typically 300 requests per 10 seconds). Large exports respect these limits but may take longer. To improve performance:

• Narrow your JQL query with date ranges or project filters

• Export only the columns you need

• Avoid overly broad queries like type != Epic

Coupler.io handles rate limiting automatically; your export will succeed but may take longer. For very large datasets, consider running exports during off-peak hours.

See best practices for optimization tips.

What happens if a Jira issue is deleted after I export it?

Deleted issues won't appear in future exports. If you need to track historical issue data, archive your export to a separate sheet or data warehouse before deleting issues in Jira.

Can I export issue history or change logs?

The current export captures the current state of each issue (status, assignee, etc.). It does not include the full change history or activity log. If you need historical data, export a snapshot regularly and compare versions, or use Jira's built-in audit log and activity history.