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Found 867 Skills
Evaluate LLM systems using automated metrics, LLM-as-judge, and benchmarks. Use when testing prompt quality, validating RAG pipelines, measuring safety (hallucinations, bias), or comparing models for production deployment.
Observability patterns for metrics, logging, distributed tracing, and error tracking. Trigger: When setting up monitoring, when implementing logging, when adding error tracking, when configuring distributed tracing, when building health checks, when creating dashboards.
Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics, analyze token usage, view LLM costs, check usage trends, or query trace statistics.
Submits and manages FastFold protein folding jobs via the Jobs API. Covers authentication, creating jobs, polling for completion, and fetching CIF/PDB URLs, metrics, and viewer links. Use when folding protein sequences with FastFold, calling the FastFold API, or scripting fold-and-wait workflows.
Analyse Datadog observability data including metrics, logs, monitors, incidents, SLOs, APM traces, RUM, security signals, and more. Use when asked to investigate infrastructure health, query metrics, search logs, check monitors, diagnose errors, or analyse any Datadog data.
Python bioinformatics library for sequence manipulation, alignments, phylogenetics, diversity metrics (Shannon, UniFrac), ordination (PCoA, CCA), statistical tests (PERMANOVA, Mantel), and biological file format I/O.
Execute ES|QL (Elasticsearch Query Language) queries, use when the user wants to query Elasticsearch data, analyze logs, aggregate metrics, explore data, or create charts and dashboards from ES|QL results.
Analytics tracking, interpretation, funnel analysis, product metrics, and ROI measurement. Use when setting up GA4/GTM tracking, interpreting analytics data, analyzing conversion funnels, calculating ROI, or measuring product engagement. Triggers on "analytics," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "funnel analysis," "conversion rates," "user flow," "cohort analysis," "retention," "product metrics," "North Star metric," "ROI," "break-even," "payback period," "investment analysis," "validate my funnel," "why isn't my funnel converting," or "executive financial report." For A/B test setup, see ab-test-setup.
Use this skill when designing backend systems, databases, APIs, or services. Triggers on schema design, database migrations, indexing strategies, distributed systems architecture, microservices, caching, message queues, observability setup, logging, metrics, tracing, SLO/SLI definition, performance optimization, query tuning, security hardening, authentication, authorization, API design (REST, GraphQL, gRPC), rate limiting, pagination, and failure handling patterns. Acts as a senior backend engineering advisor for mid-level engineers leveling up.
When the user wants to track follower growth, understand what drives new followers, or analyze audience development. Also use when the user mentions 'follower growth,' 'followers,' 'audience growth,' 'gaining followers,' 'losing followers,' 'who follows me,' or 'grow my audience.' Uses BlackTwist follower data when available. For post-level metrics, see performance-analyzer-sms. For content patterns, see content-pattern-analyzer-sms.
Generates a comprehensive client health overview across all accounts. Reads CRM data, support tickets, usage metrics, billing, and engagement logs. Calculates health scores, trend direction, and RAG status per client. Outputs a sorted risk report with recommended actions.
Write structured experiment report documents from ML/research experiment notes, configs, logs, metrics, tables, and figures. Use this skill whenever the user asks to write an experiment report, research update, mentor update, weekly experiment summary, result analysis document, or presentation-ready experiment writeup, especially when the output should explain motivation, setup, algorithms, metrics, results, figures, interpretation, conclusions, limitations, and next steps.