Aggregate and classify JSON, syslog, and Nginx logs into error clusters.
npx skills add https://github.com/haomingz/kimi-skills --skill log-diagnostic
Please help me install this Agent Skill. Skill: log-diagnostic Source: https://github.com/haomingz/kimi-skills/tree/main/skills/log-diagnostic Command: npx skills add https://github.com/haomingz/kimi-skills --skill log-diagnostic
Logs generated by applications can be noisy and fragmented across JSON, syslog, and Nginx formats; this tool unifies analysis to surface actionable error patterns.
Upload a log file to generate an error clustering, frequency, and time distribution report.
High-intent search queries and answers about installing and using this skill.
You can unify log analysis across mixed JSON, syslog, and Nginx formats by using dedicated parsers to normalize messages and detect error levels, surfacing actionable error patterns from fragmented data.
Clustering similar error messages helps reveal root causes and recurring issues by normalizing log entries and grouping them into structured clusters, making it easier to identify frequent fault patterns during incident reviews.
To generate a time distribution report for log error frequency, the system computes error occurrences over time, identifying peak problem periods to help pinpoint exactly when failures cluster in your logs.
Yes, you can generate a concise diagnostic report suitable for postmortems without custom scripts by simply uploading your log file to automatically produce error clustering, frequency, and time distribution outputs.
Yes, analyzing syslog data works for identifying peak problem periods by applying a dedicated syslog parser to normalize messages, detect error levels, and compute time distribution statistics across your logs.
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