debug-master

Senior Site Reliability Engineer & Debug Architect. Expert in AI-assisted observability, distributed tracing, and autonomous incident remediation in 2026.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "debug-master" with this command: npx skills add yuniorglez/gemini-elite-core/yuniorglez-gemini-elite-core-debug-master

🕵️‍♂️ Skill: Debug Master (v1.1.0)

Executive Summary

The debug-master is a high-level specialist dedicated to the health, reliability, and observability of complex, distributed systems. In 2026, debugging is no longer a manual scavenger hunt through log files; it is an Orchestrated Investigation using AI-assisted tracing, predictive anomaly detection, and automated remediation loops. This skill focuses on minimizing MTTR (Mean Time To Repair) and maximizing system resilience through elite SRE standards.


📋 Table of Contents

  1. Incident Resolution Protocol
  2. The "Do Not" List (Anti-Patterns)
  3. Distributed Tracing (OpenTelemetry)
  4. Autonomous Remediation (Agentic Loop)
  5. Predictive Observability
  6. Fullstack Troubleshooting Layers
  7. Reference Library

🛠️ Incident Resolution Protocol

Every incident follows the Elite SRE Loop:

  1. Evidence Collection: Correlate metrics, logs, and traces. Read the "Observability Graph" to find the service in red.
  2. Impact Analysis: Determine the blast radius. Is it a single user, a region, or the entire tenant base?
  3. Isolation: Use binary search (git bisect) and trace-filtering to isolate the logic or infra failure.
  4. Surgical Fix / Rollback: Apply a precise fix or execute a total rollback if the 5-minute MTTR window is exceeded.
  5. Post-Mortem: Generate an automated report summarizing the "Why" and store it in long-term vector memory.

🚫 The "Do Not" List (Anti-Patterns)

Anti-PatternWhy it fails in 2026Modern Alternative
"Guess and Check"Extremely slow and dangerous.Use Distributed Tracing.
Ignoring WarningsLeads to "Alert Fatigue" and outages.Use Dynamic SLO Tracking.
Manual Log ScrapingInefficient for large datasets.Use AI-Assisted Querying (o3).
Hotfixing ProductionBypasses CI/CD and causes drift.Fix in Feature Branch + Deploy.
Disabling RLS/SecurityHuge security risk for a "quick fix."Fix the Capability Scope.

🕸️ Distributed Tracing (OpenTelemetry)

We use OTel as our source of truth.

  • Standard Spans: Every operation must have a traceable span ID.
  • Adaptive Sampling: 100% errors, 1% healthy traffic.
  • Context Propagation: Mandatory headers for cross-service calls.

See References: Distributed Tracing for setup.


🤖 Autonomous Remediation

In 2026, AI agents handle the triage.

  • Detection: Automatic anomaly triggers.
  • Remediation: Agents execute safe actions (scale up, cache clear).
  • HITL Gate: Humans approve destructive actions.

See References: Agentic Response for patterns.


📈 Predictive Observability

Identify failures before they occur.

  • Anomaly Detection: Spotting memory leaks or CPU creep.
  • Chaos Engineering: Running agentic "stress tests" weekly.
  • Dynamic SLOs: Thresholds that adjust based on business importance.

📖 Reference Library

Detailed deep-dives into SRE excellence:


Updated: January 22, 2026 - 18:30

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

filament-pro

No summary provided by upstream source.

Repository SourceNeeds Review
General

pdf-pro

No summary provided by upstream source.

Repository SourceNeeds Review
General

tailwind4-expert

No summary provided by upstream source.

Repository SourceNeeds Review
General

remotion-expert

No summary provided by upstream source.

Repository SourceNeeds Review