Loading...
Loading...
Found 37 Skills
Cloud & AI FinOps advisory skill. Structured cost optimization using the FinOps Foundation framework. Covers AWS, Azure, GCP, OCI, AI inference, and data platforms (Databricks, Snowflake). Use for: cloud costs, cost optimization, cloud spend, AI costs, cloud bill, FinOps assessment, GreenOps, right-sizing, commitment strategy, tagging governance.
Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc.
Transition from static LLM chats to autonomous agents that execute multi-step tasks. Use this when you need to automate cross-platform reports (e.g., Snowflake to Google Docs), build self-service tools for non-technical teams, or create "anticipatory" engineering workflows that draft PRs based on Slack discussions.
Plan a migration onto MotherDuck. Use when moving from Snowflake, Redshift, PostgreSQL, dbt-heavy stacks, or lakehouse tooling and the key decisions are target pattern, cutover slices, validation, rollback, and native-versus-DuckLake posture.
Wire a semantic layer into a nao agent so that metric queries are routed through a single source of truth. Supports dbt MetricFlow (dbt Cloud with Semantic Layer), Snowflake (views or semantic views via MCP), an in-house nao YAML semantic layer, or other tools (via MCP discovery). Installs the right MCP server, updates RULES.md to route metric queries through the semantic layer, and (for the nao YAML option) generates starter metric files. Use after a first round of tests has shown the agent struggling with metric reliability. Do not use for raw rule writing (write-context-rules) or first-time setup (setup-context).
Build and deploy Streamlit apps natively in Snowflake. Covers snowflake.yml scaffolding, Snowpark sessions, multi-page structure, Marketplace publishing as Native Apps, and caller's rights connections (v1.53.0+). Use when building data apps on Snowflake, deploying SiS, fixing package channel errors, authentication issues, cache key bugs, or path resolution errors.
Serverless GDS sessions on Neo4j Aura — covers GdsSessions, AuraAPICredentials, DbmsConnectionInfo, SessionMemory, get_or_create, remote graph projection, gds.graph.project.remote, gds.graph.construct, algorithm execution (mutate/stream/write), async job polling, result retrieval, and session lifecycle. Use when running graph algorithms on Aura Business Critical or VDC, processing graph data from Pandas/Spark, or using the graphdatascience Python client in AGA (serverless) mode. Covers all three data source three source modes (AuraDB-connected, self-managed Neo4j, standalone from DataFrames). Does NOT cover the embedded GDS plugin on Aura Pro or self-managed Neo4j — use neo4j-gds-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover Snowflake Graph Analytics — use neo4j-snowflake-graph-analytics-skill.
Guide the user through connecting a new data warehouse source — Postgres, MySQL, Stripe, Hubspot, MongoDB, Salesforce, BigQuery, Snowflake, and so on. Use when the user wants to "connect Stripe", "import data from Postgres", "add a new data source", "sync my warehouse tables", or wants to pick sync methods for each table. Walks through source-type discovery, credential validation, table discovery, per-table sync_type selection, and the final create call. Also covers picking a good prefix and what to do right after creation.
Creates and maintains dlt (data load tool) pipelines from APIs, databases, and other sources. Use when the user wants to build or debug pipelines; use verified sources (e.g. Salesforce, GitHub, Stripe) or declarative REST API or custom Python; configure destinations (e.g. DuckDB, BigQuery, Snowflake); implement incremental loading; or edit .dlt config and secrets. Use when the user mentions data ingestion, dlt pipeline, dlt init, rest_api_source, incremental load, or pipeline dashboard.
Creates new Robot Framework test cases for SnapLogic pipeline testing. Use when the user wants to create a new test file, add test cases to existing files, or needs test templates for specific system types (Oracle, PostgreSQL, Snowflake, etc.).
Creates Robot Framework test cases for SnapLogic account creation. Use when the user wants to create accounts (Oracle, PostgreSQL, Snowflake, Kafka, S3, etc.), needs to know what environment variables to configure, or wants to see account test case examples.
Fireflies.ai platform help — AI meeting note-taker with GraphQL API, webhooks (V1 + V2), AskFred AI, real-time events, and Fred bot that joins Zoom/Meet/Teams to transcribe. Use when Fireflies transcripts not syncing to CRM, webhooks not firing or signatures failing HMAC verification, hitting 50 req/day or 60 req/min rate limits on the GraphQL API, building a transcript pipeline from Fireflies to Snowflake/BigQuery/warehouse, migrating from Webhooks V1 to V2, the Fireflies bot not joining calls or users wanting to disable auto-join, deciding between Free, Pro ($10), Business ($19), or Enterprise ($39) tier, or wiring AskFred or Real-time API into an internal app. Do NOT use for comparing Fireflies vs Fathom/Avoma/Gong or selecting a note-taker (use /sales-note-taker) or reviewing a single sales call for coaching (use /sales-call-review).