All Skills

Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

Reconstruct workflow behind a past coding-agent artifact using local ax sessions/commits/skills/tool traces. Use when asked how X was built.

Multi-cluster Kubernetes dashboard with AI-powered operations via MCP server and 10+ built-in agent skills

Methodical performance troubleshooting and root-cause analysis with Brendan Gregg's USE and TSA methods, plus evidence-backed RCA and postmortem reports.

Use when defining, reviewing, or operating SLOs/SLIs/error budgets. Triggers on "define an SLO", "what should our SLO be", "error budget", "burn rate", "SLI", "service level objective", "Google SRE workbook", "multi-window burn-rate alert", or any reliability-target question. Ships SLO designer, error-budget calculator with multi-window burn-rate thresholds, and SLO reviewer that catches the common bugs (target too aggressive, window too short, conflicting SLOs, no SLI definition). 4 references on SLO principles + SLI design + error budget math + composition with feature-flags-architect/chaos-engineering/kubernetes-operator. NOT a generic observability skill — specifically the SLO discipline.

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

Configure Sentry for comprehensive desktop application crash reporting, error monitoring, performance tracking, and release health for Electron and native desktop apps