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Found 1,864 Skills
Create an actionable Laravel implementation plan—bite-sized tasks with TDD-first steps, migrations, services, jobs, and validation points
Pre-deployment validation for Webflow Code Components. Checks bundle size, dependencies, prop configurations, SSR compatibility, styling setup, and common issues before running webflow library share.
HTTP Parameter Pollution (HPP) and JSON key duplication auditing across Express, Django, Flask, Spring, ASP.NET, and PHP backends, analyzing how front-end validators and back-end handlers resolve duplicate parameters. Use when auditing multi-layer validation and API gateways.
The HyperFrames composition contract — build one renderable project. Use for composition structure, the `data-*` timing attributes, `class="clip"`, tracks, sub-compositions, variables, framework-owned media playback, deterministic-render rules, and validation. Read before writing composition HTML.
Guide AI to generate production-quality interfaces rather than generic templates, using requirements, visual references, constraints, and iterative validation.
Implement robust forms with validation, errors, loading, submission, accessibility, and resilient UX.
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).
Provisions BigQuery datasets, ingests staged Parquet files directly into native BigQuery tables by using bq load, and deploys already-translated views from local or Cloud Storage BigQuery Migration Service (BQMS) translation outputs. Use when provisioning target BigQuery datasets for warehouse migrations, batch loading staged Parquet files into native BigQuery tables by using bq load, auditing loaded table row counts, or deploying already-translated BigQuery views into a target dataset. Don't use for extracting source database catalog metadata, translating SQL queries, views, stored procedures, or DDL schemas to GoogleSQL (use bigquery-migration-sql-translator), exporting or unloading source database tables (such as Snowflake, Databricks, Teradata, or Oracle) to Parquet on Cloud Storage, or running post-migration cross-database data validation.
Refactor Pandas code to improve maintainability, readability, and performance. Identifies and fixes loops/.iterrows() that should be vectorized, overuse of .apply() where vectorized alternatives exist, chained indexing patterns, inplace=True usage, inefficient dtypes, missing method chaining opportunities, complex filters, merge operations without validation, and SettingWithCopyWarning patterns. Applies Pandas 2.0+ features including PyArrow backend, Copy-on-Write, vectorized operations, method chaining, .query()/.eval(), optimized dtypes, and pipeline patterns.
Debug NestJS issues systematically. Use when encountering dependency injection errors like "Nest can't resolve dependencies", module import issues, circular dependencies between services or modules, guard and interceptor problems, decorator configuration issues, microservice communication errors, WebSocket gateway failures, pipe validation errors, or any NestJS-specific runtime issues requiring diagnosis.
Multi-layer validation pattern - validates data at EVERY layer it passes through to make bugs structurally impossible, not just caught.
Development cycle validation gate (Gate 5) - validates all acceptance criteria are met and requires explicit user approval before completion.