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Found 271 Skills
Detects Follow-Through Day (FTD) signals for market bottom confirmation using William O'Neil's methodology. Dual-index tracking (S&P 500 + NASDAQ) with state machine for rally attempt, FTD qualification, and post-FTD health monitoring. Use when user asks about market bottom signals, follow-through days, rally attempts, re-entry timing after corrections, or whether it's safe to increase equity exposure. Complementary to market-top-detector (defensive) - this skill is offensive (bottom confirmation).
Detects market top probability using O'Neil Distribution Days, Minervini Leading Stock Deterioration, and Monty Defensive Sector Rotation. Generates a 0-100 composite score with risk zone classification. Use when user asks about market top risk, distribution days, defensive rotation, leadership breakdown, or whether to reduce equity exposure. Focuses on 2-8 week tactical timing signals for 10-20% corrections.
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.
When the user wants to build an SEO data analysis system, monitor indexing/traffic/keywords/backlinks, or set up benchmarks. Also use when the user mentions "SEO data analysis," "SEO monitoring," "article database," "traffic benchmark," "penalty recovery," "SEO work document," "SEO dashboard," "keyword tracking," "ranking monitoring," "indexing report," or "backlink monitoring."
Estimates task effort by analyzing complexity, dependencies, historical velocity, and risk factors. Produces a structured estimate with confidence levels.
High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.
Python data analysis with pandas, numpy, and analytics libraries
Use when implementing data analysis pipelines, statistical tests, or bioinformatics workflows in code (Python/R), particularly for genomics, transcriptomics, proteomics, or other -omics data.
Query Ethereum network data via ethpandaops CLI or MCP server. Use when analyzing blockchain data, block timing, attestations, validator performance, network health, or infrastructure metrics. Provides access to ClickHouse (blockchain data), Prometheus (metrics), Loki (logs), and Dora (explorer APIs).
Event attribution and explanation. Use this skill whenever the user asks for the reason behind a price move. Trigger phrases include: why did X crash, what just happened, why is it pumping, what caused. MCP tools: news_events_get_latest_events, info_marketsnapshot_get_market_snapshot, news_events_get_event_detail, info_onchain_get_token_onchain, news_feed_search_news.
SQL query expert for optimization, schema design, and data analysis