Total 30,774 skills, Data Processing has 1471 skills
Showing 12 of 1471 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 market breadth using Monty's Uptrend Ratio Dashboard data to diagnose the current market environment. Generates a 0-100 composite score from 5 components (breadth, sector participation, rotation, momentum, historical context). Use when asking about market breadth, uptrend ratios, or whether the market environment supports equity exposure. No API key required.
Provide US dividend tax and account-location workflow for Kanchi-style income portfolios. Use when users ask about qualified vs ordinary dividends, 1099-DIV interpretation, REIT/BDC distribution treatment, holding-period checks, or taxable-vs-IRA account placement decisions for dividend assets.
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Analyzes weekly candle formation to detect red candle pullbacks and breakout signals. Supports two input modes - FMP earnings calendar (Mode A) or earnings-trade-analyzer JSON output (Mode B). Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups.
Complete 9-step Clay enrichment workflow for 90%+ data coverage plus 58 Clay templates across 8 categories. Use when building enrichment workflows, setting up Clay tables, or maximizing data quality.
Verify statistics from raw data with methodology checking, significance testing, claim validation, and bias detection. Use when fact-checking statistical claims, validating research findings, or auditing data analysis.
WNBA data via ESPN public endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, injuries, transactions, futures, team/player stats, leaders, and news. Zero config, no API keys. Use when: user asks about WNBA scores, standings, team rosters, schedules, game stats, box scores, play-by-play, injuries, transactions, betting futures, team/player statistics, or WNBA news. Don't use when: user asks about NBA (use nba-data), college basketball (use cbb-data), or other sports.
You must use this when conducting PRISMA-standard systematic reviews, protocol development, or Risk of Bias assessment.
Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.
Social media and web scraping using Apify actors. Use this skill when scraping Twitter/X tweets, Reddit posts, LinkedIn posts, Instagram profiles/posts/reels, Facebook pages/posts/groups, TikTok videos, YouTube content, Google Maps businesses/reviews, contact enrichment (emails/phones from websites), or when auto-detecting URL type to scrape. Triggers on requests to scrape social media, get trending posts, extract business info, find contact details, or extract content from social URLs.
Optimizes ClickHouse queries for speed and efficiency. Helps with primary key design, sparse indexes, data skipping indexes (minmax, set, bloom filter, ngrambf_v1), partitioning strategies, projections, PREWHERE optimization, approximate functions, and query profiling with EXPLAIN. Use when writing ClickHouse queries, designing table schemas, analyzing slow queries, or implementing analytical aggregations. Works with columnar OLAP workloads.