fixing

Automate root-cause analysis and multi-agent fix workflows for software issues.

Updated Jan 20, 2026
One-click install
npx skills add https://github.com/lukebaze/forex-rebate-bot --skill fixing-lukebaze
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fixing
Source: https://github.com/lukebaze/forex-rebate-bot/tree/main/.opencode/skill/fixing
Command: npx skills add https://github.com/lukebaze/forex-rebate-bot --skill fixing-lukebaze

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Fixing skill provides a unified framework to diagnose and fix bugs, test failures, and CI/CD issues with intelligent routing. It auto-classifies complexity and activates relevant sub-skills.

Core Features & Use Cases

  • Unified mode selection and complexity assessment to route issues to appropriate workflows.
  • Activation matrix of subagents (debugging, debugger, Explore, Bash, researcher, planner, tester, code-reviewer) to orchestrate end-to-end fixes.
  • Reproducible, step-by-step output and references guidance for CI/CD, tests, and UI issues.

Quick Start

Describe the issue clearly and start the appropriate fix workflow.

Frequently Asked Questions about fixing

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

FAQPage Schema
How do I automate root-cause analysis for CI/CD test failures?

Automating root-cause analysis for CI/CD test failures requires a multi-agent workflow that auto-classifies complexity and activates debugging, exploration, and verification subagents to orchestrate end-to-end fixes.

What is the best way to fix bugs across multiple files in a codebase?

Fixing bugs across multiple files requires a unified framework with mode selection and complexity assessment to activate relevant sub-skills like planner and code-reviewer, coordinating reproducible step-by-step output across multi-file scopes.

Can I use a human-in-the-loop approach for resolving complex UI issues?

Yes, resolving complex UI issues supports a human-in-the-loop approach. The system provides automatic mode selection but activates human-in-the-loop when needed, guided by reference materials and complexity assessment.

Does this bug-fix workflow require reference materials to guide subagents?

Yes, the bug-fix workflow requires reference materials to guide steps. It uses these references alongside mode selection and complexity assessment to activate debugging, exploration, planning, and verification subagents.

What distinguishes multi-agent bug-fix routing from manual debugging workflows?

Multi-agent bug-fix routing distinguishes itself by using an activation matrix of subagents like debugger, researcher, tester, and code-reviewer to auto-classify complexity and orchestrate reproducible fixes rather than relying on manual debugging steps.

When should I not use automated multi-agent workflows for software issues?

You should avoid automated multi-agent workflows for software issues when you lack clear reference materials or when the issue requires manual intervention outside the debugging, exploration, planning, and verification subagent scope.