gstack-openclaw-investigate

Investigate application bugs through a five-phase root cause analysis workflow.

Updated Jul 21, 2025
One-click install
npx skills add https://github.com/robertzengcn/aiFetchly --skill gstack-openclaw-investigate-robertzengcn
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: gstack-openclaw-investigate
Source: https://github.com/robertzengcn/aiFetchly/tree/main/.agents/skills/gstack/openclaw/skills/gstack-openclaw-investigate
Command: npx skills add https://github.com/robertzengcn/aiFetchly --skill gstack-openclaw-investigate-robertzengcn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates inefficient, symptom-fixing "whack-a-mole" debugging that creates recurring bugs and technical debt, ensuring you address the actual root cause of issues first.

Core Features & Use Cases

  • 5-Phase Systematic Debugging Workflow: Guides you through root cause investigation, pattern matching, hypothesis testing, minimal fix implementation, and verification with structured reporting.
  • Built-in Guardrails: Enforces rules like 3-strike hypothesis limits, no unverified fixes, and blast radius checks for changes touching more than 5 files.
  • Use Case: When your team reports a new crash in the payment processing flow, use this Skill to trace the error back to its source, avoid temporary workarounds, and implement a permanent fix with a regression test.

Quick Start

Use the gstack-openclaw-investigate skill to investigate the intermittent 500 error users encounter when submitting orders.

Frequently Asked Questions about gstack-openclaw-investigate

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

FAQPage Schema
What is root cause analysis in software debugging?

Root cause analysis in software debugging identifies the actual source of errors instead of applying temporary symptom-fixing workarounds. It prevents recurring technical debt by ensuring you address the underlying defect first through structured investigation and hypothesis validation.

How do I fix recurring bugs without creating technical debt?

To fix recurring bugs without creating technical debt, follow a systematic debugging workflow that includes pattern matching, hypothesis testing, and minimal change implementation. Enforcing rules like a 3-strike hypothesis limit and blast radius checks prevents unverified fixes and eliminates whack-a-mole debugging.

How do I create regression tests for application error investigation?

To create regression tests for application error investigation, implement them during the verification phase after applying a minimal fix to the root cause. This structured debugging process ensures the specific error trace is permanently resolved and prevents future regressions in the software development workflow.

What is the best way to investigate intermittent production crashes?

The best way to investigate intermittent production crashes is using a structured debugging process with built-in guardrails. This involves tracing error traces, validating hypotheses with a 3-strike limit, performing blast radius checks for changes touching over 5 files, and documenting the findings for development teams.

When should I not use a systematic debugging workflow?

You should avoid systematic debugging workflows when a quick workaround is explicitly required for immediate mitigation, as this process enforces strict rules like no unverified fixes and blast radius checks. It is designed for permanent defect resolution rather than rapid, temporary symptom mitigation.

Does structured debugging work for complex error trace resolution?

Structured debugging works for complex error trace resolution by enforcing a 5-phase workflow that includes investigation, pattern matching, hypothesis testing, minimal fix implementation, and structured reporting. It applies guardrails like blast radius checks to safely manage changes across multiple files.