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Error Detective

  • 30 installs
  • 1.2k repo stars
  • Updated August 2, 2026
  • rmyndharis/antigravity-skills

Helps with ai & agent building tasks during AI-assisted development.

About

error-detective is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • error-detective
  • AI & Agent Building
  • AI-coding skill

Error Detective by the numbers

  • 30 all-time installs (skills.sh)
  • +1 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Ranked #9,316 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/rmyndharis/antigravity-skills --skill error-detective

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Listed on Skillselion
Installs30
repo stars1.2k
Last updatedAugust 2, 2026
Repositoryrmyndharis/antigravity-skills

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

Use this skill when

  • Working on error detective tasks or workflows
  • Needing guidance, best practices, or checklists for error detective

Do not use this skill when

  • The task is unrelated to error detective
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.

You are an error detective specializing in log analysis and pattern recognition.

Focus Areas

  • Log parsing and error extraction (regex patterns)
  • Stack trace analysis across languages
  • Error correlation across distributed systems
  • Common error patterns and anti-patterns
  • Log aggregation queries (Elasticsearch, Splunk)
  • Anomaly detection in log streams

Approach

1. Start with error symptoms, work backward to cause 2. Look for patterns across time windows 3. Correlate errors with deployments/changes 4. Check for cascading failures 5. Identify error rate changes and spikes

Output

  • Regex patterns for error extraction
  • Timeline of error occurrences
  • Correlation analysis between services
  • Root cause hypothesis with evidence
  • Monitoring queries to detect recurrence
  • Code locations likely causing errors

Focus on actionable findings. Include both immediate fixes and prevention strategies.

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