Loading...
Loading...
Found 57 Skills
Performs gap analysis on NVIDIA TAO Visual ChangeNet (VCN) Classify experiments by invoking the data-services container (`tao_toolkit.data_services` from `versions.yaml`) directly via `docker run … gap_analysis vcn_aoi …` — picks the optimal decision threshold, ranks per-sample weakness, and emits a top-K weakest parquet expanded per-lighting for downstream augmentation. Use when analyzing VCN classification failures, picking SDA augmentation targets, auditing PASS/NO_PASS boundary cases, or running DEFT gap analysis on an AOI ChangeNet model.
Core mechanics of the Rerun Chunk Processing API (rerun.experimental) — LazyChunkStream pipelines, Chunk, lenses (MutateLens/DeriveLens/Selector), RrdReader, writing optimized RRDs. Read BEFORE writing any ingestion/conversion/preprocessing code (convert an MCAP, build a recording from a dataset, preprocess an .rrd, port an old converter): it mandates reader+lens pipelines and steers away from hand-built chunks — no Chunk.from_columns for data a reader/lens can produce, no per-message rr.log, no manual pa.array assembly. Source-specific knowledge lives in the importer skills (rerun-mcap, rerun-urdf, rerun-parquet, rerun-mp4, rerun-lerobot); read rerun-data-model first to decide what the data should become.
Salesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
Ingest a LeRobot (HuggingFace) dataset into Rerun. Read when converting a LeRobot dataset to RRDs, splitting it into per-episode segments, or registering it on a Rerun catalog. Covers the built-in directory importer (log_file_from_path), the RrdReader + send_chunks per-episode split, and when to drop to ParquetReader for custom control.
Migrates a Glue Data Catalog Hive table (Parquet) into Amazon S3 Tables as managed Iceberg using the native S3 Tables migration API (StartTableMigration, SyncTableMigration, CompleteTableMigration), a managed service call, not a self-run CTAS, Glue, or EMR job. The source is a Hive table; an Iceberg source is never in scope, even when the destination is S3 Tables. Covers plan review, migrate, sync, complete, and validate. Same-account, same-region, Glue Hive Parquet source only. Use when the request asks to migrate or import a Hive table into S3 Tables, or names the native migration API. Not applicable to converting a self-managed or standard Iceberg table into S3 Tables (ingesting-into-data-lake covers that), self-run CTAS/Glue-ETL/Spark migrations (ingesting-into-data-lake), or creating empty tables (creating-data-lake-table).
Export PostHog events, persons, sessions, or the results of a HogQL query on demand and download the resulting files. Use when the user asks to download/export raw PostHog data, export HogQL query results, create a one-off file export, fetch a Parquet or JSONLines export, or use the file_download_batch_exports API. Covers starting the export with MCP, polling completion, and downloading via the existing REST redirect endpoint.
Validates that tables migrated to BigQuery match their source (Teradata, Snowflake, Oracle, Redshift, Databricks, PostgreSQL, SQL Server, MySQL, MariaDB, Hive, Impala, Vertica) with the BigQuery Migration Service (BQMS) validation tool: schema and data type comparison, column aggregate comparison, and row-level data comparison. Use when generating or editing a validation config, running a validation, choosing sampling or partitioning, fixing connection or driver errors, or investigating validation results in BigQuery and Cloud Storage to decide which mismatches to fix. Don't use for SQL translation (use bigquery-migration-sql-translator), extracting source database catalog metadata or query logs, generating SQL scripts (such as COPY INTO) or exporting or unloading source tables to Parquet on Cloud Storage, loading staged files into BigQuery (such as bq load), or general BigQuery query failures and tuning (use bigquery-troubleshooting or bigquery-optimization).
Extracts database catalog metadata and query logs from data warehouses by running the DWH migration extractor locally or on a temporary Google Cloud VM through the BigQuery Migration Cloud Extractor (credentials held in Secret Manager), and inspects extracted `.zip` archives to report object and volume statistics. Use when extracting database metadata or query logs from Snowflake, Redshift, Teradata, Oracle, PostgreSQL, SQL Server, Hive, etc., deciding between local and cloud (Cloud Extractor) extraction, or inspecting extracted dwh-migration-*.zip archives to print post-extraction statistics. Don't use for SQL dialect translation (use bigquery-migration-sql-translator), exporting table data to Parquet or CSV files (such as Snowflake `COPY INTO` unloads) or loading it into BigQuery (use the BigQuery Data Transfer Service or bigquery-basics), or validating migrated data.
Extract raw price dataframe for a test case