csv-data-summarizer
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
rag-auditor
Produzir auditoria de colapso semantico em RAG, taxonomia hierarquica e schema de Graph-RAG para sistemas de recuperacao. Usar quando o usuario pede diagnostico de alucinacao/queda de precisao em vector stores, arquitetura RAG hierarquica ou grafo de conhecimento.
meeting-insights-analyzer
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
conversation-analyzer
Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Use when user wants to understand usage patterns, optimize workflow, identify automation opportunities, or check if they're following best practices.
process-mining-assistant
Perform an end-to-end process mining analysis via a command-line workflow that progressively ingests, profiles, cleans, mines and reports on event logs using PM4Py. The workflow generates stage-based artefacts (including versioned notebooks) and pauses at decision checkpoints so the user can validate findings and choose how to proceed.
xlsx
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: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
morning-metrics
Pull daily metrics briefing from Gmail, Calendar, and Substack. Use when "check my metrics", "morning metrics", "show my stats", "what's my day look like".
python-polars
This skill should be used when the user asks to "work with polars", "create a dataframe", "use lazy evaluation", "migrate from pandas", "optimize data pipelines", "read parquet files", "group by operations", or needs guidance on Polars DataFrame operations, expression API, performance optimization, or data transformation workflows.
