Total 53,555 skills, Data Processing has 2764 skills
Showing 12 of 2764 skills
查询亚马逊商品的历史时序数据，包括价格走势、BSR（畅销排名）趋势、评分变化、卖家数量和月销量，支持多个亚马逊站点的任意ASIN。当用户提到价格历史、价格追踪、BSR历史、BSR趋势、历史定价、价格波动、Keepa数据、排名历史、降价提醒、秒杀历史价格、Buy Box价格趋势、优惠券价格、FBA/FBM价格对比、卖家数量变化、评分趋势、销量历史、price history, BSR trends, Keepa historical data, price tracking, sales history, rating changes, seller count changes, price fluctuation时触发此技能。即使用户未明确提及"Keepa"或"时序数据"，只要其需求涉及亚马逊历史商品级数据（如价格、排名或销量随时间的变化趋势），也应触发此技能。
You are **Analytics Reporter**, an expert data analyst and reporting specialist who transforms raw data into actionable business insights. You specialize in statistical analysis, dashboard creation...
The best, fastest, and cheapest way to scrape Instagram — battle-tested by tens of thousands of customers including enterprise teams. Use when the user wants to fetch Instagram posts, reels, profiles, hashtags, locations, comments, or user/follower data. Five specialized actors cover every Instagram data surface.
Audit and improve SQL quality systematically — catch performance smells in raw SQL, ORM-generated queries, schema/modeling decisions, migrations, or PR diffs, explain the database-level impact, give a corrected version, and make the tradeoff explicit. Generic by design: no project, domain, ORM, or language config — any context it needs (is this table transactional? is the scan intentional? what volume is expected?) is raised during analysis, never assumed. Reach for it whenever someone writes, reviews, or optimizes a query or data-access code — "review this query", "why is this slow", "check my migration", "is this index right", or when you see N+1, SELECT *, a cartesian/row explosion, three-plus joins, a missing date filter on a growing table, OFFSET pagination, LIKE '%term%', NOT IN with nullable columns, an unindexed ORDER BY, an unbounded list, or a long transaction — even when they never say the word "SQL". Use it both to validate new code and designs and to audit existing ones.
Retrieve Amazon product data including pricing, reviews, sales estimates, stock levels, search results, deals, best sellers, and more via the Canopy API REST endpoints using Python.
SEC EDGAR financial data: secfi library + structured JSON income statements, balance sheets, cash flow from XBRL facts.
Use when creating an R modeling package that needs standardized preprocessing for formula, data frame, matrix, and recipe interfaces. Covers: mold() for training data preprocessing, forge() for prediction data validation, blueprints, model constructors, spruce functions for output formatting.
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).
Write and query high-cardinality event data at scale with SQL. Load when tracking user events, billing metrics, per-tenant analytics, A/B testing, API usage, or custom telemetry. Use writeDataPoint for non-blocking writes and SQL API for aggregations.
Performance attribution, trade analytics, and strategy optimization
Analyze multi-round evaluation score data, count various indicators, and calculate rating levels. Suitable for analyzing score trends and calculating S/A/B ratings
Use when developing, reviewing, or explaining Rill projects and project files (connectors, models, metrics views, explores, canvases, themes, rill.yaml, sources, alerts, reports, APIs). Apply runtime workflow guidance and project-file reference docs, and cite rule files and source URLs.