How a Quality Assistant Bot Streamlines Cross‑Team Jira Management with Enterprise WeChat

1. Why

Cross‑team projects often face difficult quality control due to many bug types, cumbersome statistics, and limited communication.

Bug types are many, statistics are cumbersome

Various legacy and online bugs appear in each iteration.

Manual filtering and classification require repeated pushes when quality thresholds are not met.

Cross‑team collaboration suffers from limited quality communication

As the company grows, more projects involve multiple business lines. For example, the Tool Integration 4.0 project spans several lines. Each release must meet quality red‑line standards, but communication between lines is scarce; clear visibility of each line's quality status reduces communication cost.

Quality Assistant features

Daily quality: improve cross‑team quality communication.

Online timeout faults: automatically collect fault count, days, severity, and @mention the responsible person in group chat.

Offline bugs unresolved for 30 days: automatically collect similar information and notify the assignee.

2. How we built it

Information acquisition

· Create a public filter, e.g., http://jira.qunhequnhe.com/issues/?filter=XXXX

· Parse Jira data such as bug count, assignee, and creation time.

Information delivery

· Add the Quality Assistant bot to a group chat.

· The bot sends messages with the collected information.

Challenges encountered

How to obtain information

1. Jira REST API request: https://docs.atlassian.com/software/jira/docs/api/REST/6.4.7/

2. jira‑rest‑java‑client‑api library: https://docs.atlassian.com/jira-rest-java-client/1.0/apidocs/

· Filter condition changes: request filter API to get JQL, e.g., http://jira.qunhequnhe.com/rest/api/2/filter/15748

· Use

searchResult

from jira‑rest‑java‑client‑api to obtain issues under the filter.

· Extract needed fields (status, assignee, priority, creationDate) from issueDetails.

3. Current results

Current outcomes

1. Deployed in 7 business lines, 29 agile teams, stable for 10 months.

2. Effectively reduced resolution time for offline bugs and online faults, decreasing fault persistence.

Future plans

Self‑service configuration UI.

Support custom filter and schedule settings.

Collect broader requirements, such as alerts for individuals with excessive bugs.