Total 55,032 skills, Data Processing has 2818 skills
Showing 12 of 2818 skills
Calculate Economic Order Quantity to minimize total inventory cost (ordering + holding). Use this skill when the user needs to determine optimal order size, balance ordering frequency against storage costs, or set reorder points — even if they say 'how much to order', 'optimal batch size', or 'inventory cost minimization'.
Analyze financial health using ratio categories: profitability, liquidity, leverage, efficiency, and valuation. Use this skill when the user needs to assess a company's financial performance, compare companies, evaluate creditworthiness, or prepare financial due diligence — even if they say 'is this company financially healthy', 'analyze these financial statements', or 'compare these two companies'.
Apply Difference-in-Differences (DID) to estimate causal treatment effects by comparing changes in outcomes between treatment and control groups. Use this skill when the user evaluates policy interventions, natural experiments, or regulatory changes, needs to test parallel trends, or when they ask 'did this policy work', 'how do I identify causal effects without randomization', or 'what is the treatment effect'.
Points to the BlockchainSpider open-source Python/Scrapy toolkit for collecting on-chain data—transfer subgraphs around an address or tx, EVM and Solana block/transaction ingestion, receipts/logs, and optional label plugins. Use when the user wants to build datasets, offline traces, or research pipelines alongside blockchain-analytics-operations and solana-tracing-specialist—not as a substitute for RPC provider ToS, rate limits, or legal review of sensitive crawls.
Cointegration testing for pairs trading using Engle-Granger, Johansen, and rolling stability analysis
Create, manage, and deploy Power BI semantic models inside Microsoft Fabric workspaces via `az rest` CLI against Fabric and Power BI REST APIs. Use when the user wants to: (1) create a semantic model from TMDL definition files, (2) retrieve or download semantic model definitions, (3) update a semantic model definition with modified TMDL, (4) trigger or manage dataset refresh operations, (5) configure data sources, parameters, or permissions, (6) deploy semantic models between pipeline stages. Covers Fabric Items API (CRUD) and Power BI Datasets API (refresh, data sources, permissions). For read-only DAX queries, use `powerbi-consumption-cli`. For fine-grained modeling changes, route to `powerbi-modeling-mcp`. Triggers: "create semantic model", "upload TMDL", "download semantic model TMDL", "refresh dataset", "semantic model deployment pipeline", "dataset permissions", "list dataset users", "semantic model authoring".
Create analytics question files (.question.yml) in Steedos projects. Questions are report/chart definitions stored as YAML seed data files, based on the @steedos-labs/analytics package (Metabase engine). Covers file format, dataset_query structure (MBQL), display types, visualization_settings, result_metadata, and file naming conventions.
Trace the citation neighborhood around one focal paper into foundations, descendants, bridges, weak edges, and optional second-hop links
Expert guidance for creating, modifying, and optimizing dbt pipelines for BigQuery. Use this skill whenever user asks for generating or modifying a dbt model or project. Activate this skill when the user - Creates, modifies, or troubleshoots **dbt models or pipelines** - Needs to **optimize SQL** within a dbt project - Is **setting up a new dbt project** or configuring existing one
Use when reading from or writing to Neo4j with Apache Spark or Databricks using the Neo4j Connector for Apache Spark (org.neo4j:neo4j-connector-apache-spark). Covers SparkSession setup, DataFrame reads via labels/Cypher/relationship scan, DataFrame writes with SaveMode, node.keys for MERGE, relationship write mapping, partition and batch tuning, PySpark and Scala examples, Databricks cluster config, Databricks secrets for credentials, Delta Lake to Neo4j pipelines. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT handle the Python bolt driver — use neo4j-driver-python-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
Detect and classify candlestick patterns from ingested OHLCV data