Total 30,538 skills, Data Processing has 1462 skills
Showing 12 of 1462 skills
Parse, transform, and analyze CSV files with advanced data manipulation capabilities.
Analyze the BTC market using a custom momentum theory with nested multi-timeframe analysis (2-day/1-day/12h/6h/4h/2h/1h/30min). Identify uptrend segments, downtrend segments, discrete regulation, unit adjustment cycles, continuous gap divergences, and DIF-DEA divergences, and generate momentum reports with detailed attribute judgments and trading signals. Automatically activates when users inquire about BTC momentum, segment status, MACD analysis, cycle judgment, or divergence detection.
Bright Data Web Scraper API via curl. Use this skill for scraping social media (Twitter/X, Reddit, YouTube, Instagram, TikTok), account management, and usage monitoring.
Use when designing database schemas, need to model domain entities and relationships clearly, building knowledge graphs or ontologies, creating API data models, defining system boundaries and invariants, migrating between data models, establishing taxonomies or hierarchies, user mentions "schema", "data model", "entities", "relationships", "ontology", "knowledge graph", or when scattered/inconsistent data structures need formalization.
This skill should be used when the user asks to "analyze crypto", "analyze market trends", "analyze btc", "look at eth", "check sol", or mentions cryptocurrency technical analysis. It provides market maker perspective analysis using Binance API data.
For the creation, review, refactoring, and presentation of .ipynb Notebooks (Jupyter / JupyterLab / Google Colab / VS Code). Covers engineered directory structures, efficient token processing, demonstration/sharing patterns, and reproducible workflows with uv/venv.
Diagnose ClickHouse disk usage, compression efficiency, part sizes, and storage bottlenecks. Use for disk space issues and slow IO.
Adds schema tests and data quality validation to dbt models. Use when working with dbt tests for: (1) Adding or modifying tests in schema.yml files (2) Task mentions "test", "validate", "data quality", "unique", "not_null", or "accepted_values" (3) Ensuring data integrity - primary keys, foreign keys, relationships (4) Debugging test failures or understanding why dbt test failed Matches existing project test patterns and YAML style before adding new tests.
Creates dbt models following project conventions. Use when working with dbt models for: (1) Creating new models (any layer - discovers project's naming conventions first) (2) Task mentions "create", "build", "add", "write", "new", or "implement" with model, table, or SQL (3) Modifying existing model logic, columns, joins, or transformations (4) Implementing a model from schema.yml specs or expected output requirements Discovers project conventions before writing. Runs dbt build (not just compile) to verify.
Safely refactors dbt models with downstream impact analysis. Use when restructuring dbt models for: (1) Task mentions "refactor", "restructure", "extract", "split", "break into", or "reorganize" (2) Extracting CTEs to intermediate models or creating macros (3) Modifying model logic that has downstream consumers (4) Renaming columns, changing types, or reorganizing model dependencies Analyzes all downstream dependencies BEFORE making changes.
Debugs and fixes dbt errors systematically. Use when working with dbt errors for: (1) Task mentions "fix", "error", "broken", "failing", "debug", "wrong", or "not working" (2) Compilation Error, Database Error, or test failures occur (3) Model produces incorrect output or unexpected results (4) Need to troubleshoot why a dbt command failed Reads full error, checks upstream first, runs dbt build (not just compile) to verify fix.
Documents dbt models and columns in schema.yml. Use when working with dbt documentation for: (1) Adding model descriptions or column definitions to schema.yml (2) Task mentions "document", "describe", "description", "dbt docs", or "schema.yml" (3) Explaining business context, grain, meaning of data, or business rules (4) Preparing dbt docs generate or improving model discoverability Matches existing project documentation style and conventions before writing.