Verified:GitHub

investigate-with-jira

Coordinate parallel codebase exploration to trace Jira bug tickets to root causes.

2|Updated Apr 11, 2026

Search Tags:#root cause analysis #parallel agents #jira #bug investigation #codebase exploration #read-only investigation #serena search

Ready to run

npx skills add https://github.com/wilsonfaustino/ai-tools --skill investigate-with-jira

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: investigate-with-jira
Source: https://github.com/wilsonfaustino/ai-tools/tree/main/skills/investigate-with-jira
Command: npx skills add https://github.com/wilsonfaustino/ai-tools --skill investigate-with-jira

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually tracing the root cause of Jira bug tickets across large codebases is time-consuming, often misses cross-layer issues, and requires deep context switching for engineers.

Core Features & Use Cases

Parallel orthogonal exploration: Fans out read-only Sonnet agents across 3 non-overlapping code layers (data model/API, filter/predicate logic, UI consumer chain) to avoid redundant work.
Ranked root-cause report: Synthesizes agent findings into a prioritized list of suspect code locations, explicitly rules out false trails, and flags unresolved open questions.
Use case: When a Jira bug is reported with no clear source, use this skill to quickly identify if the issue originates in API data shapes, client-side filtering, or UI rendering, without modifying any code.

Quick Start

Use the investigate-with-jira skill to trace the root cause of Jira bug P40-60664, providing the context that the bug only occurs when filtering by active status.

Frequently Asked Questions about investigate-with-jira

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I trace the root cause of a Jira bug in a large codebase?▼

Tracing the root cause of a Jira bug is automated by coordinating parallel read-only agents across data models, filter logic, and UI components to pinpoint suspect code locations without modifying code.

How does parallel agent codebase exploration work for bug investigation?▼

Parallel agent codebase exploration works by fanning out read-only agents across three non-overlapping code layers: data model/API, filter/predicate logic, and UI consumer chain, synthesizing their findings into a prioritized list of suspect code locations.

What do I need to start investigating Jira tickets with Serena search?▼

To start investigating Jira tickets, you need a valid Jira ticket identifier, optional owner-supplied context, and access to Atlassian MCP and Serena symbol search tools for efficient symbol-level code traversal.

Can I use this approach to find bugs across API data shapes and UI rendering?▼

Yes, you can use this approach to find bugs across API data shapes and UI rendering, as the parallel agents specifically trace reported defects to their source in data models, filter logic, or UI components.

Does root cause analysis with parallel agents modify my source code?▼

No, root cause analysis with parallel agents is strictly read-only, meaning it traces reported defects to their source without editing code or updating Jira tickets.

What is the best way to investigate cross-layer issues from Jira bug reports?▼

The best way to investigate cross-layer issues from Jira bug reports is using parallel orthogonal exploration, which fans out read-only agents across non-overlapping code layers to avoid redundant work and synthesize a ranked root-cause report.