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Found 675 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.
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.
Monitor Granola usage, analytics, and meeting insights. Use when tracking meeting patterns, analyzing team productivity, or building meeting analytics dashboards. Trigger with phrases like "granola analytics", "granola metrics", "granola monitoring", "meeting insights", "granola observability".
Production-ready phylogenetics and sequence analysis skill for alignment processing, tree analysis, and evolutionary metrics. Computes treeness, RCV, treeness/RCV, parsimony informative sites, evolutionary rate, DVMC, tree length, alignment gap statistics, GC content, and bootstrap support using PhyKIT, Biopython, and DendroPy. Performs NJ/UPGMA/parsimony tree construction, Robinson-Foulds distance, Mann-Whitney U tests, and batch analysis across gene families. Integrates with ToolUniverse for sequence retrieval (NCBI, UniProt, Ensembl) and tree annotation. Use when processing FASTA/PHYLIP/Nexus/Newick files, computing phylogenetic metrics, comparing taxa groups, or answering questions about alignments, trees, parsimony, or molecular evolution.
Set up PostHog metrics plan with event funnel, KPI benchmarks, and kill/iterate/scale decision thresholds. Use when user says "set up metrics", "track KPIs", "PostHog events", "funnel analysis", "when to kill or scale", or "success metrics". Do NOT use for SEO metrics (use /seo-audit).
Calculate influencer campaign ROI and build a leadership-ready narrative summary from raw performance data. This skill should be used when calculating ROI for a creator campaign, building a campaign performance report for leadership, turning raw influencer metrics into an executive summary, computing CPM CPE ROAS and EMV for a creator program, summarizing campaign spend versus revenue for a stakeholder meeting, proving influencer marketing ROI to a CMO or VP, creating a campaign wrap report with financial metrics, or comparing influencer channel efficiency against paid social. For setting KPI targets before a campaign launches, see performance-benchmark-setter. For tracking creator posting compliance, see creator-posting-compliance-tracker. For full end-of-campaign reporting with qualitative analysis, see post-campaign-creator-scorecard. For building UTM links to enable attribution, see utm-parameter-builder.
Use when the user needs to inspect Google Cloud (GCP) logs, metrics, and monitoring signals via gcloud for incident triage, debugging, or operational analysis. Supports Cloud Logging queries, Cloud Monitoring time-series reads, and environment checks for a target project.
Captures quality metrics baseline (tests, coverage, type errors, linting, dead code) by running quality gates and storing results in memory for regression detection. Use at feature start, before refactor work, or after major changes to establish baseline. Triggers on "capture baseline", "establish baseline", or PROACTIVELY at start of any feature/refactor work. Works with pytest output, pyright errors, ruff warnings, vulture results, and memory MCP server for baseline storage.
Detect Single Responsibility Principle (SRP) violations using multi-dimensional analysis. Use when reviewing code for "SRP", "single responsibility", "god class", "doing too much", "too many dependencies", before commits, during refactoring, or as quality gate. Analyzes Python, JavaScript, TypeScript files with AST-based detection, metrics (TCC, ATFD, WMC), and project-specific patterns. Provides actionable fix guidance with refactoring estimates.
Complete ClickHouse operations guide for DevOps and SRE teams managing production deployments. Provides practical guidance on monitoring essential metrics (query latency, throughput, memory, disk), introspecting system tables, performance analysis, scaling strategies (vertical and horizontal), backup/disaster recovery, tuning at query/server/table levels, and troubleshooting common issues. Use when diagnosing ClickHouse problems, optimizing performance, planning capacity, setting up monitoring, implementing backups, or managing production clusters. Includes resource management strategies for disk space, connections, and background operations plus production checklists.
Diagnose SaaS business health using key metrics, identify red flags, and prioritize actions. Analyzes growth, retention, efficiency, and capital health.