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debugging-toolkit-smart-debug

Guide AI-assisted triage and root-cause analysis using observability data.

Updated Apr 12, 2026
Search Tags:#workflow#debugging#troubleshooting#observability#triage#root-cause-analysis#ai-assisted
One-click install
npx skills add https://github.com/BoraPerusic/agents --skill debugging-toolkit-smart-debug-boraperusic
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: debugging-toolkit-smart-debug
Source: https://github.com/BoraPerusic/agents/tree/main/skills/to%20try/debugging-toolkit-smart-debug
Command: npx skills add https://github.com/BoraPerusic/agents --skill debugging-toolkit-smart-debug-boraperusic

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Streamlines the diagnosis of complex software issues by guiding AI-assisted triage, data collection, and stepwise investigation.

Core Features & Use Cases

  • Interactive triage that identifies likely root causes and suggests next steps.
  • Observability-driven debugging that leverages logs, traces, metrics, and environment data.
  • Structured workflow for hypothesis generation, instrumentation planning, validation, and prevention.

Quick Start

Describe your debugging issue, provide relevant logs and traces, and let the AI suggest a prioritized plan.

Frequently Asked Questions about debugging-toolkit-smart-debug

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

FAQPage Schema
What is AI-assisted debugging and how does it help with root-cause analysis?▼

AI-assisted debugging uses artificial intelligence to guide triage, evidence collection, and stepwise investigation, streamlining root-cause analysis in complex software systems by suggesting prioritized plans and hypotheses.

How do I debug complex software issues in production or staging environments?▼

To debug complex software issues in production or staging, describe your problem and provide relevant observability data like logs and traces. The workflow then guides safe instrumentation, triage, and validation of fixes.

Can I use observability data like logs, traces, and metrics for troubleshooting?▼

Yes, observability-driven troubleshooting leverages logs, traces, metrics, and environment data to identify likely root causes, generate hypotheses, and suggest next steps for resolving complex software issues.

What is the best way to structure a debugging workflow for hypothesis generation?▼

The best way to structure a debugging workflow is through stepwise investigation: interactive triage, hypothesis generation, instrumentation planning, validation, and prevention, guided by AI-assisted analysis.

Does this debugging approach work for safe production debugging across multiple components?▼

Yes, this approach applies to safe production debugging across multiple components, supporting triage, observability-driven data gathering, and validation of fixes within complex staging or production environments.

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