field-extraction-parsing
CommunityTurn unstructured logs into structured data.
Authorrustomax
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill converts unstructured log text into structured, queryable fields using OPAL's extraction and parsing functions, enabling reliable data analysis, filtering, and correlation across large log datasets.
Core Features & Use Cases
- Named-capture extraction with extract_regex() to create new columns from log lines.
- Delimited data handling with split() and split_part() to break apart paths, CSV-like data, and identifiers.
- JSON support with parse_json() and JSONPath navigation to access nested fields in JSON-embedded logs.
- Practical workflows: parse timestamps, IDs, metrics, and nested values for observability and incident analysis.
Quick Start
Use a representative log line and an OPAL workflow to extract fields (timestamps, levels, IDs) and to access nested JSON values using JSONPath.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: field-extraction-parsing Download link: https://github.com/rustomax/observe-community-mcp/archive/main.zip#field-extraction-parsing Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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