菜单
Composite pipeline skill that chains log-parser and csv-stats-reporter to filter JSONL logs and compute response-time statistics in a single step.
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基于 SOC 职业分类
Validate tabular data against configurable business rules — range checks, cross-column constraints, referential integrity against lookup tables, and temporal consistency.
Load and parse CSV files into structured data frames with configurable encoding, delimiter, and date parsing options.
Export pandas DataFrames or processed datasets to well-formatted CSV files with configurable encoding, delimiter, quoting, and column ordering.
Aggregate tabular data by one or more dimensions with configurable metrics — sum, mean, count, min, max, median. Supports multi-level grouping and pivot table generation.
Comprehensive data cleaning toolkit — handles missing values, duplicate removal, type coercion, whitespace trimming, and outlier detection in a single pass over the dataset.
Identify and remove duplicate records from tabular datasets using exact-match, fuzzy-match, or composite-key-based deduplication strategies.
| name | log-health-analyzer |
| description | Composite pipeline skill that chains log-parser and csv-stats-reporter to filter JSONL logs and compute response-time statistics in a single step. |
| version | 1.0.0 |
A composite pipeline skill that orchestrates two existing skills — log-parser and csv-stats-reporter — into a single unified workflow. Given a JSONL server log file, this skill:
This eliminates the repetitive two-step manual process of parsing logs then running statistics separately.
| Order | Skill | Role |
|---|---|---|
| 1 | log-parser | JSONL → filtered CSV |
| 2 | csv-stats-reporter | filtered CSV → stats JSON report |
| Parameter | Flag | Required | Source Skill | Description |
|---|---|---|---|---|
| input | -i | Yes | log-parser | Path to the input .jsonl log file |
| output | -o | Yes | csv-stats-reporter | Path to the output JSON stats report |
| start-time | --start | No | log-parser | Start of time window (e.g. 09:00) |
| end-time | --end | No | log-parser | End of time window (e.g. 17:00) |
| levels | --levels | No | log-parser | Comma-separated severity filter (e.g. ERROR,WARN) |
| columns | --columns | No | csv-stats-reporter | Numeric columns to analyse (default: all) |
| group-by | --group-by | No | csv-stats-reporter | Column to group statistics by (e.g. service) |
| keep-csv | --keep-csv | No | pipeline | Keep the intermediate filtered CSV file |
log-parser on the input JSONL file with
the specified time range and severity filters. Output goes to a temporary CSV.csv-stats-reporter on the filtered
CSV with the specified columns and group-by settings. Output goes to the final
JSON report.--keep-csv is specified.A JSON stats report (same format as csv-stats-reporter output) containing
per-column metrics for the filtered log events.
python3 ./skills/log-health-analyzer/log_health_analyzer.py \
-i <input.jsonl> -o <stats_report.json> \
[--start HH:MM] [--end HH:MM] [--levels ERROR,WARN] \
[--columns response_time_ms] [--group-by service] [--keep-csv]
log-parser, csv-stats-reporter