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Found 487 Skills
Browser automation with Puppeteer CLI scripts. Use for screenshots, performance analysis, network monitoring, web scraping, form automation, or encountering JavaScript debugging, browser automation errors.
This skill should be used when adding error tracking and performance monitoring with Sentry and OpenTelemetry tracing to Next.js applications. Apply when setting up error monitoring, configuring tracing for Server Actions and routes, implementing logging wrappers, adding performance instrumentation, or establishing observability for debugging production issues.
Automatically sync Agents.md, claude.md and gemini.md files in the project to maintain content consistency. Supports automatic monitoring and manual triggering.
Know when your AI breaks in production. Use when you need to monitor AI quality, track accuracy over time, detect model degradation, set up alerts for AI failures, log predictions, measure production quality, catch when a model provider changes behavior, build an AI monitoring dashboard, or prove your AI is still working for compliance. Covers DSPy evaluation for ongoing monitoring, prediction logging, drift detection, and alerting.
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
Generate analytics reports from Olakai data using CLI commands. AUTO-INVOKE when user wants: usage summaries, KPI trends, risk analysis, ROI reports, efficiency metrics, agent comparisons, token usage reports, cost analysis, compliance reports, or any analytics without using the web dashboard. TRIGGER KEYWORDS: olakai, analytics, reports, usage summary, KPI trends, risk analysis, ROI, efficiency, agent comparison, token usage, cost analysis, metrics report, dashboard data, CLI analytics, terminal report, compliance, usage report, event summary, performance metrics, AI usage stats. DO NOT load for: setting up monitoring (use olakai-add-monitoring), troubleshooting (use olakai-troubleshoot), or creating new agents (use olakai-create-agent).
Performance optimization and continuous improvement for sobriety.tools recovery app. Use for load time optimization, offline capability, crisis detection, performance monitoring, automated issue detection. Activate on "sobriety.tools", "recovery app perf", "crisis detection", "offline meetings", "HALT check-in", "sponsor contacts". NOT for general Next.js help, unrelated Cloudflare Workers, or non-recovery apps.
Reporting framework for monitoring trust, sentiment, and regulator-facing KPIs.
Track Clawdbot AI model usage and estimate costs. Use when reporting daily/weekly costs, analyzing token usage across sessions, or monitoring AI spending. Supports Claude (opus/sonnet), GPT, and Codex models.
Git-centric implementation workflow. Enforces clean checkout, creates a properly named branch, tracks progress in a WIP markdown file, and commits continuously so git logs serve as the primary monitoring channel. Use when starting instructed, offer for any plan-based implementation task.
Git-centric implementation workflow. Enforces clean checkout, creates a properly named branch, tracks progress in a WIP markdown file, and commits/pushes continuously so remote git logs serve as the primary monitoring channel. Use when starting any plan-based implementation task.
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.