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Found 869 Skills
End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (monitoring and retraining).
Measure and improve how well your AI works. Use when AI gives wrong answers, accuracy is bad, responses are unreliable, you need to test AI quality, evaluate your AI, write metrics, benchmark performance, optimize prompts, improve results, or systematically make your AI better. Covers DSPy evaluation, metrics, and optimization.
Translates engineering metrics (DORA, error rates, technical debt) into business KPIs and financial impact. Helps justify technical investments to stakeholders.
Display session efficiency report showing token savings, cache performance, and optimization recommendations. Use when user asks "show my stats", "how efficient am I?", "show session metrics", or wants to see Navigator's impact.
Compare FinOps metrics across multiple repositories in an organization
Query Mozilla telemetry data directly from BigQuery using the bq CLI. Use when the user wants to run SQL against Firefox telemetry, analyze Windows version distribution, count DAU/MAU/WAU, query Glean metrics, or investigate user populations. Triggers on "bigquery", "bq", "telemetry query", "DAU", "MAU", "Windows distribution", "macOS distribution", "Darwin version", "Linux distribution", "kernel version", "client count", "user count", "Glean metrics query", "baseline_clients".
Set up comprehensive observability for Fireflies.ai integrations with metrics, traces, and alerts. Use when implementing monitoring for Fireflies.ai operations, setting up dashboards, or configuring alerting for Fireflies.ai integration health. Trigger with phrases like "fireflies monitoring", "fireflies metrics", "fireflies observability", "monitor fireflies", "fireflies alerts", "fireflies tracing".
Validate Godot GDScript files using gdlint, gdformat, gdradon, and LSP diagnostics. Use when users want to: (1) Check code quality after making changes, (2) Validate before committing, (3) Run code metrics analysis, (4) Run export validation, (5) Get real-time LSP diagnostics. Uses command-line tools directly and MCP tools for LSP integration.
Use this skill when the user needs to design onboarding flows, define their aha moment, improve activation rates, or reduce early churn. Covers activation metrics, interactive onboarding, personalization, progressive disclosure, and first-run UX.
Monitor use when you need to work with monitoring and observability. This skill provides health monitoring and alerting with comprehensive guidance and automation. Trigger with phrases like "monitor system health", "set up alerts", or "track metrics".
Design experiment plans with progressive stages — initial implementation, baseline tuning, creative research, and ablation studies. Plan baselines, datasets, hyperparameter sweeps, and evaluation metrics. Use when planning experiments for a research paper.
System metrics, telemetry, and performance monitoring