Data & Analytics

ivanshamaev Skill

AIOps autonomous query cost analyzer — Trino system.runtime.query_history cost SQL (CPU time/peak memory/bytes scanned), ClickHouse system.query_log top expensive queries, Spark UI cost attribution by user/job/DAG, BigQuery INFORMATION_SCHEMA.JOBS cost analysis, LLM-driven query rewrite recommendations (missing partition filters/broadcast hints/aggregation pushdown), cost anomaly detection (user over daily budget), automated query tagging, chargeback report by team/project

ivanshamaev Skill

Airflow + StarRocks data quality gates — post-load row count validation, freshness checks (MAX(updated_at) vs expected), null explosion detection, duplicate key audit on Primary Key tables, volume anomaly detection (z-score vs 7-day avg), SODA-style SQL quality checks embedded in DAG, quarantine pattern for bad partitions

ivanshamaev Skill

Use when writing, reviewing, debugging, or optimizing SQL for Vertica — covering DDL (CREATE/ALTER/DROP TABLE, columns, projections, segmentation, partitions), DML (INSERT, UPDATE, DELETE, MERGE, TRUNCATE, COPY), CRUD patterns, and Vertica-specific performance guidance including encoding, segmentation keys, partition pruning, and query optimization.

ivanshamaev Skill

Soda Core data quality — SodaCL checks (row_count, missing, invalid, duplicate, freshness, schema, reference, custom SQL), configuration.yml for PostgreSQL/Spark/ClickHouse/BigQuery, soda scan CLI, Airflow integration, dbt integration, alerting

ivanshamaev Skill

Use when writing, reviewing, debugging, or optimizing production Spark SQL for Hive/lakehouse/HDFS tables, including CTE-heavy queries, joins, windows, partition pruning, Hive Metastore operations, insert/overwrite safety, query hints, statistics, EXPLAIN plans, AQE, skew, materialization, and SQL performance diagnostics.

ivanshamaev Skill

StarRocks data quality — freshness queries (MAX(updated_at) vs expected SLA), duplicate detection on Primary Key tables, null anomaly SQL (column-level null rate vs baseline), volume drift detection (day-over-day ratio), cross-table referential integrity checks, data completeness for partitions, StarRocks-specific quality checks (tablet health, compaction lag, replication factor), Python DQ scan class

ivanshamaev Skill

StarRocks lakehouse integration — Iceberg/Hive/Delta external catalogs (HMS/Glue/REST), cross-catalog INSERT INTO SELECT, partition filter pushdown verification, external table statistics (ANALYZE on Iceberg), writing back to Iceberg from StarRocks (3.1+), Delta Lake catalog setup, Unity Catalog (3.2+), query federation across StarRocks + Iceberg + Hive in single SQL, cache invalidation (REFRESH EXTERNAL TABLE)

ivanshamaev Skill

Use when designing, implementing, reviewing, or optimizing production PySpark ETL/DataFrame pipelines at GB-TB+ scale, including schemas, joins, partitioning, window functions, writes, UDF avoidance, and Spark performance diagnostics.

ivanshamaev Skill

Apache Airflow DAG authoring — DAG definition, TaskFlow API (@task/@dag decorators), operators (Bash/Python/SQL/HTTP), sensors (poke/reschedule modes), TaskGroups, dynamic task mapping (expand/partial), branching, trigger rules, XComs, Pools, callbacks, cross-DAG pipelines, best practices

ivanshamaev Skill

MLflow for data engineering — tracking server setup (PostgreSQL backend + S3 artifacts), experiment tracking (params/metrics/artifacts/autolog), ETL job metadata logging (row counts, DQ metrics, lineage tags), Model Registry (register/alias/promote), model serving (pyfunc/REST API/batch scoring), MLproject files, Airflow integration (MLflowClientHook/XCom/model promotion), Spark integration (mlflow.spark.autolog/log_model/Delta metadata)

taipt1504 Bundle

Database patterns for Java Spring — R2DBC (reactive), JPA/Hibernate (servlet), PostgreSQL, MySQL, connection pooling (HikariCP/r2dbc-pool), Flyway migrations, and query optimization. Use when writing @Entity or R2DBC models, creating Repository interfaces, writing @Query methods, planning Flyway migrations, tuning connection pools, or reviewing SQL performance. Includes scripts/validate-migration.sh for migration file validation.

ivanshamaev Skill

Airflow + StarRocks ETL best practices — idempotent DAG design (label strategy/partition overwrite), retry with backoff, SLA callbacks, dynamic partition creation, duplicate prevention with MERGE/INSERT OVERWRITE, DAG-level concurrency controls, dependency ordering, catchup safety, data lineage tagging

ivanshamaev Skill

Use when optimizing, diagnosing, or reviewing Vertica 11.x SQL query performance — covering EXPLAIN plan reading, projection design for predicates/joins/GROUP BY/ORDER BY/analytic functions, segmentation strategies, column encoding, RLE, sort elimination, Top-K, INSERT-SELECT tuning, DELETE/UPDATE internals, and Data Collector diagnostics.

ivanshamaev Skill

Trino warehouse cost optimization — query scan cost analysis (system.runtime.queries/system.runtime.tasks), identifying expensive queries by CPU time and data scanned, scan reduction via partition pruning and file compaction, worker autoscaling patterns (scale-to-zero for batch), spot instance strategies for workers, S3 object storage cost (storage vs request costs), Iceberg compaction economics (fewer splits = fewer S3 GET requests), cost attribution by team/user, materialized view break-even analysis, result caching

ivanshamaev Skill

Trino distributed SQL query optimization — predicate/projection/aggregation pushdown, join reordering (AUTOMATIC/ELIMINATE_CROSS_JOINS), broadcast vs partitioned joins, dynamic filtering, CBO with ANALYZE, filter-early patterns, partition pruning, avoiding SELECT *, reducing shuffle, cross-catalog query cost, session property tuning, query hints, anti-patterns for slow Trino queries

ivanshamaev Skill

dbt + StarRocks testing — generic tests (not_null/unique/accepted_values/relationships), singular tests (custom SQL assertions), source freshness tests (loaded_at_field), StarRocks-specific volume and freshness tests, dbt-expectations integration, test severity (warn vs error), store_failures for debugging failed tests, ANALYZE before test runs, partition-scoped test SQL

ivanshamaev Skill

StarRocks Stream Load — HTTP PUT API (curl/Python requests), CSV/JSON format parameters (column_separator/jsonpaths/strip_outer_array), columns mapping, partial_update for Primary Key tables, label idempotency, max_filter_ratio, timeout tuning, merge commit mode (3.4+), response JSON parsing, Python bulk loader pattern, error diagnosis

anilveersingh1308 Bundle

Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when asked to "review this PR", "code review", "pre-landing review", or "check my diff". Proactively suggest when the user is about to merge or land code changes. (gstack)

houjingyi00417-hub Skill

GPU-accelerate Python code using CuPy, Numba CUDA, Warp, cuDF, cuML, cuGraph, KvikIO, cuCIM, cuxfilter, cuVS, cuSpatial, and RAFT. Use whenever the user mentions GPU/CUDA/NVIDIA acceleration, or wants to speed up NumPy, pandas, scikit-learn, scikit-image, NetworkX, GeoPandas, or Faiss workloads. Covers physics simulation, differentiable rendering, mesh ray casting, particle systems (DEM/SPH/fluids), vector/similarity search, GPUDirect Storage file IO, interactive dashboards, geospatial analysis, medical imaging, and sparse eigensolvers. Also use when you see CPU-bound Python code (loops, large arrays, ML pipelines, graph analytics, image processing) that would benefit from GPU acceleration, even if not explicitly requested.

houjingyi00417-hub Skill

Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.

houjingyi00417-hub Skill

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

houjingyi00417-hub Skill

Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.

houjingyi00417-hub Skill

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

houjingyi00417-hub Skill

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.

houjingyi00417-hub Skill

All-in-one web toolkit powered by parallel-cli, with a strong emphasis on academic and scientific sources. Use this skill whenever the user needs to search the web, fetch/extract URL content, enrich data with web-sourced fields, or run deep research reports. Covers: web search (fast lookups, research, current info 鈥?prioritizing peer-reviewed papers, preprints, and scholarly databases), URL extraction (fetching pages, articles, academic PDFs), bulk data enrichment (adding fields to CSV/lists from the web), and deep research (exhaustive multi-source reports grounded in academic literature). Also handles setup, status checks, and result retrieval. Use this skill for ANY web-related task 鈥?even if the user doesn't mention 'parallel' or 'web' explicitly. If they want to look something up, fetch a page, enrich a dataset, investigate a topic, find academic papers, check citations, or review scientific literature, this is the skill to use.

l3mpire Skill

Scrapes structured data from any website and exports it to a clean CSV file. Use this skill whenever the user provides a URL and wants to extract specific information from it — even if they just say "scrape this site", "extract all the contacts from this page", "get me the pricing from this URL", "pull all the job listings", or "grab the data from this website into a CSV". Handles single pages, paginated results, sitemaps, and multi-page scraping. Always produces a downloadable CSV file as output.

l3mpire Skill

Detects, scores, and resolves duplicate contacts and company accounts in CRM systems. Use this skill whenever the user mentions duplicate records, dirty CRM data, double contacts, merged accounts, data quality issues, or asks to "clean up the CRM", "find duplicates", "deduplicate contacts", or "fix our HubSpot / Salesforce data". Accepts CSV exports, HubSpot MCP, or Salesforce MCP as input. Produces a scored duplicate report, a field-level merge plan, a bulk merge CSV, and prevention rules.

l3mpire Skill

Scans Claap call transcripts to surface expansion and upsell opportunities for the Claap sales team. Use this skill whenever the user wants to find leads hidden in existing customer or prospect calls — even if they just say "trouve des opportunités de vente dans mes calls", "qui pourrait acheter Claap dans mes recordings", "cherche des signaux d'achat dans claap", "analyse mes transcripts pour trouver des leads", or "qui est pas satisfait de son note taker". Always fetches transcripts via the Claap MCP, scores each call against a set of buying signals, and outputs a structured CSV plus a ranked opportunity table.

hugocantor Bundle

Map FMPROD and FMDEL green-screen fields to Db2 for i SQL UDTFs, Kotlin API endpoints, Angular UI fields, and documentation. Use when comparing legacy screens with REST calls, TF_FMPROD* objects, product inquiry/status behavior, field mappings, maintenance screens, or docs/fmprod analysis under /home/hcantor/Projects.

hugocantor Bundle

Add, review, or explain Kotlin Spring Boot API endpoints in apiv1 that call Db2 for i table functions. Use when working with UDTFs, TF_* SQL objects, GET endpoints, controllers, services, repositories, row mappers, OpenAPI, JT400, Spring JDBC, or API contract updates under /home/hcantor/Projects/apis/apiv1.

bc05 Bundle

Use esta skill ao transformar arquivos .sql alterados na diff local em uma migration Supabase. Aplica os SQLs no banco local, executa supabase db diff para gerar uma nova migration e decide o idioma do nome analisando as migrations existentes.

bahadir-digital Skill

Yüklenen dashboard, rapor verisi veya KPI tablosunu yöneticiler için 3 cümlelik insight'lara dönüştüren skill. Operasyonel veri yöneticiye sunulurken "neden önemli, ne değişti, ne yapmalıyız" sorularını cevaplar. Excel, CSV, dashboard ekran görüntüsü veya tablo yüklendiğinde tetiklenir. BI uzmanları, raporlama ekipleri, operasyon yöneticileri için.

bahadir-digital Skill

Yüklenen Excel veya CSV dosyasındaki tekrarlayan kayıtları, hatalı formatları, eksik verileri ve boşlukları tespit edip temizleme önerileri sunan ve temizlenmiş versiyonu oluşturan skill. Veri analisti olmayan beyaz yakalılar için en sık ihtiyaç duyulan işlerden biri. Excel veya CSV dosyası yüklendiğinde otomatik tetiklenir.

showarm Bundle

Generate a styled Excel report of Cursor usage by session for a given month or date range. Reads JSONL session logs from ~/.cursor/projects/**/agent-transcripts/, pulls token-level usage events from api2.cursor.sh (using the local IDE access token in vscdb), attributes events to sessions by timestamp, summarizes each session via cursor-agent (Haiku), and outputs an XLSX to the Desktop. Use this when the user asks for a Cursor usage report — phrases like "帮我总结X月份我的cursor报告", "总结我X月份的Cursor使用", "出X月Cursor报表", "我这个月在Cursor里做了什么", "summarize my Cursor usage for [period]".

nicolasestrem Skill

a senior SQL developer with mastery across major database systems (PostgreSQL, MySQL, SQL Server, Or

bruhxax Skill

Use whenever creating dashboards, admin panels, analytics pages, SaaS interfaces, data layouts, widgets, tables, metrics, charts, or management interfaces. Creates cleaner, more structured, less cluttered dashboard layouts.