Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or get distribution stats.
npx skills add https://github.com/zebbern/claude-code-guide --skill log-error-digest
Automated log file analysis that produces error clustering, frequency statistics, and time distribution reports.
| Format | Description | Auto-detection |
|--------|-------------|----------------|
| JSON | One JSON object per line with timestamp/level/message fields | Starts with { |
| syslog | RFC 3164 format, e.g. Jan 1 12:00:00 host proc[pid]: msg | Starts with month name |
| Nginx | Access log or error log format | Starts with IP or date/path pattern |
python scripts/analyze_logs.py <log_file_path> [options]
| Parameter | Description | Default |
|-----------|-------------|---------|
| log_file | Path to the log file (required) | - |
| --format | Log format: auto/json/syslog/nginx | auto |
| --top | Show Top N error clusters | 20 |
| --output | Export results to a JSON file | Terminal output only |
| --level | Filter by log level (e.g. ERROR, WARN) | All levels |
| --since | Only analyze logs after this time (ISO format) | No limit |
| --until | Only analyze logs before this time (ISO format) | No limit |
# Auto-detect format and analyze the entire log file
python scripts/analyze_logs.py /var/log/app.log
# Specify Nginx format, show only Top 10 errors
python scripts/analyze_logs.py /var/log/nginx/error.log --format nginx --top 10
# Filter ERROR level only, export JSON report
python scripts/analyze_logs.py app.log --level ERROR --output report.json
# Analyze logs within a specific time range
python scripts/analyze_logs.py app.log --since 2024-01-01T00:00:00 --until 2024-01-02T00:00:00
=======================================================
Log Analysis Report
=======================================================
📊 Overview
Detected format: json
Total lines: 15,234
Parsed: 15,100 (parse failures: 134)
Matched entries: 12,800
Errors: 2,341
Time range: 2024-01-01 00:03:12 ~ 2024-01-01 23:58:45
🔴 Top Error Clusters (47 total)
#1 [×523 ] Connection refused to database at 10.0.1.5:5432
First seen: 2024-01-01T00:15:30 Last seen: 2024-01-01T23:45:12
#2 [×312 ] Timeout waiting for response from user-service after 30000ms
First seen: 2024-01-01T02:10:00 Last seen: 2024-01-01T22:30:45
#3 [×198 ] File not found: /data/uploads/img_99421.png
First seen: 2024-01-01T08:00:00 Last seen: 2024-01-01T20:15:33
...
⏰ Time Distribution (by hour)
00:00 █████░░░░░░░░░░░░░░░ 42
01:00 ██░░░░░░░░░░░░░░░░░░ 18
...
14:00 ████████████████████ 523
...
📅 Time Distribution (by date)
2024-01-01 ████████████████████ 2,341
Use the --output parameter to export a structured JSON report for further processing or integration with monitoring systems.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
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Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
Take zebbern/log-error-digest from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.