debugDebug errors and performance. Use when tracing log errors, parsing stack traces, detecting memory leaks, or profiling commands.
Install via ClawdBot CLI:
clawdbot install bytesagain/debugGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Accesses system directories or attempts privilege escalation
/var/log/Calls external URL not in known-safe list
https://bytesagain.comAI Analysis
The skill's primary functions involve local log analysis, stack trace parsing, and process monitoring, which align with its stated debugging purpose. The external URL (homepage) is for attribution, not an active API call, and accessing /var/log/ is a legitimate requirement for log analysis tools, not an attempt at privilege escalation.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 20, 2026
During a system outage, operations teams can use the trace command to scan application logs for error patterns like FATAL, OOM, or Exception. This quickly identifies error frequency and types, helping prioritize fixes by showing the last 20 matching lines and unique patterns with timestamps normalized for deduplication.
Developers debugging crashes in polyglot microservices can pipe stack traces through the stacktrace command to auto-detect languages like Python, Java, or Go. It extracts error messages and call chains with file/line references, speeding up root cause analysis without manual parsing of different trace formats.
DevOps engineers suspecting memory issues can use the leaks command to monitor a process's RSS and VSZ over time with configurable intervals. It flags leaks with growth thresholds (>20% for possible, >5% for moderate), providing a time-series table and summary to validate fixes during deployment or scaling events.
CI/CD teams can profile command execution times, such as build or test runs, using the profile command with repeat options for statistical accuracy. It reports min/avg/max timings with speed classifications (FAST, MODERATE, SLOW), helping optimize pipelines and identify performance regressions across deployments.
After deploying updates, QA engineers can compare pre- and post-deploy logs with the diff-logs command, focusing on errors-only to catch newly introduced issues. It shows line count differences and new/removed entries, ensuring deployments don't introduce warnings or fatal errors into production systems.
Integrate this debug skill into a SaaS platform's monitoring suite, offering it as a premium feature for automated log analysis and incident response. Revenue is generated through subscription tiers based on usage volume, with upsells for advanced analytics and real-time alerts on error patterns.
Provide consulting services to enterprises for implementing and customizing the debug tool in their DevOps workflows. Revenue comes from hourly rates for setup, training, and ongoing support, with packages for incident response and performance optimization audits.
Offer the core debug skill as open source to build community adoption, then monetize through enterprise editions with additional features like GUI dashboards, team collaboration tools, and compliance reporting. Revenue is driven by licensing fees for these enhanced versions.
💬 Integration Tip
Ensure all required Unix tools (curl, openssl, ps) are installed and accessible in the environment; for cloud deployments, package the skill with a lightweight container to maintain portability across different systems.
Scored Apr 19, 2026
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