Data & Analytics

davila7 Skill

Scan the codebase for common security issues: hardcoded secrets, SQL injection vectors, XSS, unvalidated inputs, and insecure defaults. Use before deploying, as part of code quality review, or when asked to check for security issues.

hiai-gg Skill

Diagnose why a PostgreSQL query is slow or suspicious: understand the SQL, inspect tables and indexes, EXPLAIN JSON, and propose measured next steps. Use when a query is slow, timing out, or has a suspicious plan.

sidetoolco Skill

Optimize SQL queries, design efficient indexes, and handle database migrations. Solves N+1 problems, slow queries, and implements caching. Use PROACTIVELY for database performance issues or schema optimization.

snowflake-labs Bundle

Use when designing or refactoring Snowflake RBAC: choosing a role hierarchy, creating database/schema access roles, setting up functional roles, deciding between primary and secondary roles, or referencing roles in masking and row access policies. Routes to focused sub-flows for each layer of the hierarchy. Triggers: rbac, role hierarchy, access roles, functional roles, schema access role, database access role, warehouse access role, secondary roles, policy roles, role design, grant, managed access schema, future grants

snowflake-labs Bundle

Use for **ALL** Snowflake documentation lookups: feature questions, SQL syntax, best practices, how-to guides, configuration, and troubleshooting. This is the required entry point for any question about Snowflake products or features. Triggers: Snowflake docs, how do I, SQL syntax, CREATE, ALTER, DROP, warehouse, stage, Cortex, Snowpipe, dynamic table, stored procedure, UDF, MCP, Snowpark, Streamlit, Native App, data sharing, replication, security, roles, grants, what is, how does, Snowflake feature.

snowflake-labs Bundle

Use when a user pastes a Snowflake Quickstart URL or asks to learn/walk through a Quickstart. Fetches the source content from GitHub, parses it into stages, checks the learner's environment, and delivers a guided build experience with two modes (learner or builder). Triggers: quickstarts.snowflake.com, snowflake.com/en/developers/guides/, walk me through this quickstart, teach me this quickstart, learn this guide, I want to do this quickstart. Do NOT use for general SQL help or non-Quickstart tutorials.

snowflake-labs Bundle

Audits all (or selected) Cortex Agents in a Snowflake account. For each agent the skill reads the live specification, extracts every dependency (semantic views, Cortex Search services, UDFs, warehouses, tables), then checks whether a user-supplied role holds the required privilege on each object — including inherited grants via role hierarchy. Results are presented as a gap table grouped by agent, followed by an optional one-click remediation script. Triggers: check agent access, audit agent privileges, who can use my agents, role access to agents, missing agent grants, grant agent usage, agent USAGE check, PUBLIC can't call agent, fix agent permissions, check role permissions for Cortex Agent. Do NOT use for: general RBAC design (use `rbac`), warehouse credit audits, or auditing non-agent Snowflake objects.

snowflake-labs Bundle

Snowpark Connect (SCOS) skills for migrating and validating PySpark, Spark Scala, and Spark Java workloads on Snowflake. Generates SMA-compatible reports (Issues.csv, InputFilesInventory.csv, ArtifactDependencyInventory.csv) using EWI codes (SPRKCNTPY* for Python, SPRKCNTSCL* for Scala/Java) for use with dvp-sma-dashboard-generator. Use when: migrating PySpark or Spark Scala/Java to Snowpark Connect, validating SCOS migrations, analyzing Spark compatibility, assessing a Spark workload before migration, producing a migration readiness report, or working with Snowpark Connect for Spark. Triggers: snowpark connect, scos, pyspark migration, spark connect, scala spark migration, java spark migration, spark java, validate migration, pyspark compatibility, scala compatibility, java compatibility, assess pyspark, assess spark, assess databricks, spark assessment, databricks assessment, migration readiness, spark workload assessment, pyspark readiness, spark compatibility report, analyze spark, analyze pyspark, analyz

snowflake-labs Bundle

Migrate PySpark and Databricks workloads to Snowflake SCOS (Snowpark Connect for Spark). Use when: converting Spark code to run on Snowflake, analyzing PySpark compatibility, updating imports to Spark Connect equivalents, or migrating from Databricks. Generates SCOS-compatible reports (Issues.csv, InputFilesInventory.csv, ArtifactDependencyInventory.csv) for the dvp-scos-dashboard-generator using official SCOS EWI codes (SPRKCNTPY*). Triggers: migrate pyspark, convert spark, scos migration, spark connect, pyspark compatibility, snowpark connect.

snowflake-labs Bundle

Migrate Spark Java workloads to Snowflake SCOS (Snowpark Connect for Spark). Use when: converting Java Spark code to run on Snowflake, analyzing Java Spark compatibility, updating imports to Spark Connect equivalents, or migrating from standalone Spark Java. Generates SMA-compatible reports (Issues.csv, InputFilesInventory.csv, ArtifactDependencyInventory.csv) for the dvp-sma-dashboard-generator using official SMA EWI codes (SPRKCNTSCL* — JVM family). Triggers: migrate java spark, convert java spark, scos java migration, spark connect java, java compatibility, snowpark connect java.

snowflake-labs Bundle

Migrate Spark Scala workloads to Snowflake SCOS (Snowpark Connect for Spark). Use when: converting Scala Spark code to run on Snowflake, analyzing Scala Spark compatibility, updating imports to Spark Connect equivalents, or migrating from standalone Spark Scala. Generates SMA-compatible reports (Issues.csv, InputFilesInventory.csv, ArtifactDependencyInventory.csv) for the dvp-sma-dashboard-generator using official SMA EWI codes (SPRKCNTSCL*). Triggers: migrate scala spark, convert scala, scos scala migration, spark connect scala, scala compatibility, snowpark connect scala.

wardawgmalvicious Bundle

Use for Fabric Materialized Lake Views (MLVs) — `CREATE MATERIALIZED LAKE VIEW` Spark SQL (GA March 2026) + still-preview `@fmlv.materialized_lake_view` PySpark decorator on a schema-enabled lakehouse (Runtime 1.3). Covers CREATE / SHOW / ALTER RENAME / DROP / REFRESH FULL syntax, `CONSTRAINT ... CHECK ... ON MISMATCH DROP|FAIL` data quality rules, partitioning/TBLPROPERTIES, optimal refresh (skip/incremental/full) + CDF prerequisite, the supported-SQL-constructs table, lineage-driven dependency ordering, scheduling (time-based vs event-triggered Preview, per-schedule Spark environment, Extended lineage across lakehouses/workspaces), `RefreshMaterializedLakeViews` REST job-type, run history (25 runs / 7 days), data quality report, gotchas: no ALTER definition only RENAME, no DML/UDF/temp views/time-travel, all-uppercase schemas rejected, names lowercased, `spark.conf.set` ignored on refresh, 24-hour run cap, overlapping refreshes skipped, PySpark always full-refresh, deleting defining notebook breaks refresh.

wardawgmalvicious Skill

Review code for correctness, naming conventions, style, error handling, security, and scaling concerns. Use when reviewing code, checking a diff, auditing a function, or asking about code quality. Covers Python, PySpark, SQL, KQL, DAX, and data-engineering patterns.

wardawgmalvicious Bundle

Use when troubleshooting Microsoft Fabric — common errors: 401 (wrong token audience), 403 on Power BI API (Viewer role), 404 EntityNotFound (permissions masquerading), PowerBIEntityNotFound (logicalId vs runtime ID), Login failed (wrong Initial Catalog), 24556/24706 snapshot conflict, nvarchar/datetime/money errors (Warehouse unsupported types), COPY INTO auth, MERGE/ALTER COLUMN failures, TMDL validation (tabs vs spaces, /// comments), DefaultJob jobType mistake, sqlcmd version, slow SQLEP (small files), notebook `400 exceptionCulprit:1` (bare-string cell source), Variable Library `InvalidContent (ValueMismatch)` (stale override / empty value), greyed-out deployment-rule dropdowns (Direct Lake), DirectQuery-transformations refresh error, PBIR-Legacy format, MissingDefinitionParts, empty visuals after publish (byConnection rebind), empty Top-N visuals + frozen save (bad TopN filter), RTDB `baseQueryId` error, Runtime 2.0 `LibraryManagementError` (republish environment), plus MUST/PREFER/AVOID summary.

wardawgmalvicious Bundle

Use for the Fabric security/permission model. Covers the layers (workspace roles Admin/Member/Contributor/Viewer, item-level Read/ReadData/ReadAll, OneLake security data access roles, SQL GRANT/DENY/REVOKE), Admin/Member/Contributor bypass of RLS/CLS/DDM, least-privilege pattern (Viewer + SQL GRANT), ReadData vs ReadAll distinction (SQL vs Spark/OneLake), the mode-dependent RLS/CLS enforcement across engines (OneLake security GA May 2026 enforces in Spark/Lakehouse/Direct-Lake-on-OneLake and SQL endpoints in user's-identity mode; the old Spark/OneLake bypass survives only for SQL-defined RLS and delegated-identity-mode endpoints), auto-create of users on GRANT (no CREATE USER), and the 40-warehouses-per-workspace token-size limit.

wardawgmalvicious Bundle

Use for Microsoft Fabric Eventhouse / KQL Database. Covers connection (cluster URI via `kqlDatabases` REST, kusto.kusto.windows.net audience, az rest temp-file for `|` escaping), authoring (`.create-merge` for safe schema evolution, ingestion inline/set-or-append/from-storage `;impersonate`, streaming policy, CSV/JSON mappings, retention/caching/partitioning/merge policies, materialized views + update policies, external tables), OneLake-availability-ON constraints (add/delete column ✅ April 2026+; type/rename/RLS/deletes need availability off), per-KQL-database remote MCP server (http, read/query auth, not in global MCP template), 4-role permissions (viewer/user/ingestor/admin), KQL query patterns (time-filter-first, has vs contains, materialize), string-matching speed table, KQL graph operators (`make-graph`/`graph-match`/`graph()` snapshots, openCypher — in-engine KQL graph, NOT the GraphModel item; see fabric-graph), and Fabric gotchas (`;impersonate`, MV stuck at 0%, dynamic vs string, == case-sensitive).

wardawgmalvicious Bundle

Use for diagnosing Fabric Spark performance through the monitoring REST APIs — listing Livy sessions (/workspaces/{ws}/spark/livySessions with queuedDuration/runningDuration, HC_ session naming), pulling the Spark History Server mirror (notebooks, sparkJobDefinitions or lakehouses → .../livySessions/{livy}/applications/{appId}/jobs, plus /stages, /executors, /sql) for job timelines and gap analysis, attributing notebook wall-clock to queue/boot/work/teardown phases, verifying high-concurrency session reuse (sessionSource created vs reused), and the sibling log and resourceUsage routes (coreEfficiency, idleTime, Livy/driver/executor logs).

wardawgmalvicious Bundle

Use for monitoring Fabric Warehouse queries — OPTION (LABEL = '...') for tracking, the queryinsights schema (exec_requests_history, exec_sessions_history, long_running_queries, frequently_run_queries), 30-day retention, 15-minute appearance lag, the `Invalid object name` gotcha on newly-created warehouses, and diagnosing slow/stale Lakehouse SQLEP reads under the new metadata-sync preview (`sys.dm_db_external_tables_log_status`, `sp_dw_refresh_ext_table`).

davesnx Bundle

Write, edit, or analyze posts and threads for X, including audience fit, supplied analytics, and verified recommendation-system constraints. Use for X-content requests and diagnosis. Treat algorithm details as constraints and never promise reach. Do not use for developer documentation, which belongs to technical-docs, or for independent evidence gathering and cited technical findings.

docevilock Bundle

Multi-platform social media data crawling tool (Xiaohongshu, Douyin, Kuaishou, Bilibili, Weibo). Use when you need to search for posts, extract details, or scrape comments from supported platforms. Supports managing authentication (Cookies, QR codes) and saving data in JSON, CSV, or Excel formats.

dragoon0x Skill

Use when designing, auditing, or refactoring data tables, grids, lists of tabular data, sortable columns, or any structured-data display. Covers the table vs card decision, density, row height, alignment, sorting, pagination, sticky headers, zebra striping, responsive behavior, and empty states. Trigger when the user mentions table, data grid, rows, columns, spreadsheet, list view, or data table.

1398281322-a11y Skill

Use when optimizing 接口性能, N+1 SQL/RPC, 循环远程调用, Hikari 连接池, 批量写入, or 同步转异步. Do not use for GC (backend-jvm-prod), EXPLAIN (backend-mysql-index), or incident 排查顺序 (backend-observability).

1398281322-a11y Skill

Use when writing or reviewing APIs that touch authz, 越权, SQL injection, third-party callback signatures, 核销 merchant ownership, or sensitive fields. Use on almost every write API; skip only for internal read prototypes with no user input.

1398281322-a11y Skill

Use when diagnosing slow SQL, creating or changing secondary indexes, EXPLAIN, 最左前缀, covering index, or implicit conversion. Do not use for sharding or table status-machine design.

1398281322-a11y Skill

Use when defining API 接口规范, REST methods, HTTP status, 错误码, 版本, pagination, 金额单位分, 时区, Idempotency-Key, or request_id. Do not use for HMAC/replay (backend-api-security) or SQL 越权 (backend-safe-check).

1398281322-a11y Skill

Use when deciding 下单扣库存 vs 支付扣库存 vs 预占/锁定库存, 可售库存, 锁定库存, occupy TTL. Do not replace the SQL condition stock>=n (backend-concurrency-sell). Do not use for 秒杀分层 (backend-seckill).

1398281322-a11y Skill

Use when cluster login state, 分布式 Session, JWT, SSO, Redis session, sticky sessions, or gateway auth is in play. Do not use for SQL 越权 resource checks (backend-safe-check).

anthonyalcaraz Bundle

Budget a specialist model fleet against the two production bottlenecks: KV-cache-bound concurrency and end-to-end latency. Computes how many concurrent users a GPU can host (peak KV per active user, not model size, is the binding constraint), proves that quantizing weights does not move that ceiling while KV compression (MEMENTO) does, estimates GPU speedups for graph analytics (cuGraph / nx-cugraph), and checks a multi-node workflow against the book's latency budget and the sub-2s target. Use when scaling a multi-model agent to real-time latency. NOT for model selection (that is model-routing-selector), NOT for cost/quality scoring (that is cost-performance-scorer), NOT for defining GPU terms (that is gpu-glossary-anchor).

ardurai Bundle

God-level backend engineering: Node.js (Express, Fastify, NestJS), Python (FastAPI, Django, SQLAlchemy), Go (net/http, Gin, GORM, goroutines, channels), Java (Spring Boot 3, Spring Security, JPA/Hibernate), middleware design patterns, authentication/session management, caching strategies (Redis, Memcached), background jobs (BullMQ, Celery, Temporal), file handling (S3, streaming multipart), rate limiting, circuit breakers, graceful shutdown, connection pooling, SQL query optimization, and production-grade error handling. Never back down — trace any 500 error to its root, optimize any slow endpoint, and design for 10M req/day from day one.

ardurai Bundle

God-level database mastery covering SQL (PostgreSQL deep dive, MySQL differences), NoSQL (MongoDB, Cassandra, DynamoDB), NewSQL (CockroachDB, Spanner), caching (Redis deep dive — data structures, persistence, clustering, pub/sub), message streaming (Apache Kafka — architecture, partitioning, consumer groups, exactly-once semantics), Elasticsearch/OpenSearch (indexing, mapping, search relevance, aggregations), time-series (InfluxDB, TimescaleDB), graph databases (Neo4j), schema design, query optimization, indexing strategies, ACID vs BASE, CAP theorem, replication, sharding, and connection pooling. A developer who does not understand their database is a developer who will eventually bring it to its knees.

reagin Bundle

Implement or review Go relational-database code using database/sql, pgx, sqlx, or an existing data layer. Use for query safety, scanning and nullability, transactions, pools, migrations, performance, and database tests while preserving the project's selected datastore and library.

ryanduguid Bundle

Use when pulling, specifying, or validating the source exports the contracting pack runs on: job or tracking-dimension P&L, contract and claim registers, plant registers and hire dockets, payroll by employee and by job, and subcontractor payment listings, including file conventions, completeness checks and CSV parsing traps. Reference skill for the other skills in this pack.

incidentfox Bundle

Google BigQuery data warehouse queries and schema inspection. Use when running SQL queries, listing datasets/tables, or inspecting table schemas in BigQuery.

incidentfox Bundle

Snowflake data warehouse queries and schema inspection. Use when running SQL queries against Snowflake, listing tables, or inspecting schemas.

incidentfox Bundle

Amplitude product analytics. Use when querying user events, funnels, retention, or product usage data. Provides event segmentation, user activity lookup, and annotation queries.

incidentfox Bundle

Incident.io incident management and analytics. Use for listing, searching, and analyzing incidents. Supports MTTR calculations, severity analysis, and alert fatigue detection via alert route analytics.