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Found 1,660 Skills
Apply PyGraphistry graph ML/AI workflows such as UMAP, DBSCAN, embedding-based anomaly analysis, and fit/transform pipelines on nodes or edges. Use for feature-driven exploration, clustering, anomaly triage, and graph-AI notebook workflows.
Shotstack integration. Manage Deals, Persons, Organizations, Leads, Projects, Pipelines and more. Use when the user wants to interact with Shotstack data.
Covalent integration. Manage Organizations, Projects, Pipelines, Users, Goals, Filters. Use when the user wants to interact with Covalent data.
Streak integration. Manage Persons, Organizations, Deals, Pipelines, Users, Roles. Use when the user wants to interact with Streak data.
Fireberry integration. Manage Organizations, Pipelines, Users, Goals, Filters. Use when the user wants to interact with Fireberry data.
OnceHub integration. Manage Leads, Persons, Organizations, Deals, Pipelines, Activities and more. Use when the user wants to interact with OnceHub data.
End-to-end prospect research pipeline: Apollo enrichment → personalized email + call scripts → draft review → Apollo sequence load. Eliminates manual research bottleneck. Use when: 'research prospect', 'prospect [company]', 'build cadence for', 'outreach for [company]', 'research-to-cadence', 'enrich and sequence', 'new prospect batch'.
Design GCP architectures for startups and enterprises. Use when asked to design Google Cloud infrastructure, deploy to GKE or Cloud Run, configure BigQuery pipelines, optimize GCP costs, or migrate to GCP. Covers Cloud Run, GKE, Cloud Functions, Cloud SQL, BigQuery, and cost optimization.
Design Azure architectures for startups and enterprises. Use when asked to design Azure infrastructure, create Bicep/ARM templates, optimize Azure costs, set up Azure DevOps pipelines, or migrate to Azure. Covers AKS, App Service, Azure Functions, Cosmos DB, and cost optimization.
Melo integration. Manage Organizations, Pipelines, Users, Goals, Filters. Use when the user wants to interact with Melo data.
Use when agent instruction files (AGENTS.md, rules/) need analysis, trimming, or restructuring. Orchestrates /imperatives → /policy-algebra → /visualize into a distillation pipeline.
Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where S3 Tables is not adopted. Handles one-time loads, recurring pipelines, migrations. Triggers on: import data, load data, ingest, sync database, migrate table, move data to AWS, set up pipeline, ETL, pull from Snowflake, query BigQuery into S3, export DynamoDB, CTAS, convert to Iceberg. Do NOT use for setting up or troubleshooting Glue connections (use connecting-to-data-source), creating empty tables (use creating-data-lake-table), running queries (use querying-data-lake), finding tables by fuzzy name (use finding-data-lake-assets), catalog audit (use exploring-data-catalog), or SaaS platforms like Salesforce, ServiceNow, SAP, MongoDB, Kafka.