Découvrez les skills blockchain data analysis, comparez leurs dépôts et consultez leurs instructions.
Unified visual content system for cardiology thought leadership. Automatically routes requests to the optimal tool—Fal.ai for blog imagery, Gemini for infographics, Mermaid for flowcharts/pathways, Marp for sli...
Generate world-class medical infographics using carousel-level visual language. Templates include hero stats, multi-section layouts, comparisons, myth-busters, process flows, and patient checklists. Default 108...
Create Domino Launchers - parameterized web forms for self-service job execution. Enable business users to run analyses, generate reports, and trigger batch predictions without coding. Covers parameter types, e...
Analiza ejercicios matemáticos tipo ICFES según 6 dimensiones oficiales (dificultad, competencia, componente, pensamiento, contenido, eje). Usa cuando tengas imagen de problema ICFES, pregunta matemática para c...
Create structured visualizations of stakeholder perspectives (says, thinks, does, feels) to build deep understanding. Use when conducting user research or validating assumptions.
Transform raw research into actionable insights that inform design decisions. Use during Define phase after completing research.
Generates SHANNON_INDEX for 94% token reduction (58K → 3K tokens). Compresses large codebases into structured summaries with Quick Stats, Tech Stack, Core Modules, Dependencies, Recent Changes, and Key Patterns...
Use when performing meta-analysis, pooling study data, generating forest plots, funnel plots, assessing heterogeneity, or conducting subgroup and sensitivity analyses. Invoke for any statistical synthesis of mu...
Comprehensive financial statement analysis including ratio calculation, trend analysis, and peer comparison. Evaluates liquidity, profitability, efficiency, and leverage metrics. Requires numpy>=1.24.0, pandas>...
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for...
Analyze Excel spreadsheets, create pivot tables, generate charts, and perform data analysis. Use when analyzing Excel files, spreadsheets, tabular data, or .xlsx files.
Analyze a project to provide a summary of line counts per programming language (e.g., how many lines of Go vs Rust). Generates a PDF summary report.
Generate, validate, and refine Mermaid diagrams (flowcharts, sequence diagrams, class diagrams, state diagrams, Gantt charts, ERD, component diagrams). Use when creating visualizations, documenting workflows, s...
Common patterns for extracting and combining analytics data from GA4, GSC, and SE Ranking. Includes API patterns, rate limiting, caching, and error handling.
Specialized skill for analyzing personal health data, medical records, lab results, and supplement protocols. Use when working with health records, clinical data, lab values, or health optimization planning.
Analyze metrics, create reports, and track KPIs. Builds dashboards, revenue models, and growth projections. Use PROACTIVELY for business metrics or investor updates.
Data analysis expert for SQL queries, BigQuery operations, and data insights. Use proactively for data analysis tasks and queries.
Work with Resource datasets (mutable state tracking) using OPAL temporal joins. Use when you need to enrich Events/Intervals with contextual state information, track resource state changes over time, or navigat...
Aggregate and summarize event datasets (logs) using OPAL statsby. Use when you need to count, sum, or calculate statistics across log events. Covers make_col for derived columns, statsby for aggregation, group_...
Master OPAL window functions for row-relative calculations, rankings, and moving aggregates. Covers lag(), lead(), row_number(), rank(), dense_rank(), moving averages, first(), and last(). Use when comparing ro...
Detect anomalies in metrics and time-series data using OPAL statistical methods. Use when you need to identify unusual patterns, spikes, drops, or outliers in observability data. Covers statistical outlier dete...
Analyze percentile metrics (tdigest type) using OPAL for latency analysis and SLO tracking. Use when calculating p50, p95, p99 from pre-aggregated duration or latency metrics. Covers the critical double-combine...
Work with Interval datasets (time-bounded data) using OPAL. Use when analyzing data with start and end timestamps like distributed traces, batch jobs, or CI/CD pipeline runs. Covers duration calculations, tempo...
Work with Reference Tables (static CSV lookup data) using OPAL to enrich datasets with descriptive information. Use when you need to map IDs to human-readable names, add static metadata from CSV uploads, or per...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.