Explorar skills

Auto-activate for litestar_saq imports, SAQPlugin, SAQConfig, QueueConfig, TaskQueues, CronJob, litestar workers run, background jobs, scheduled jobs, or SAQ web UI. Use when adding first-party SAQ background work to Litestar. Not for Celery, RQ, Dramatiq, raw SAQ outside Litestar, or custom PostgreSQL-native queues unless explicitly chosen.

Auto-activate for SQLAlchemyAsyncRepositoryService, SQLSpecAsyncService, create_filter_dependencies, LimitOffsetFilter, OffsetPagination, repository_type, service_class, filters, pagination, or CRUD service layers. Use when implementing Litestar data services, repositories, filters, or pagination. Not for raw driver usage with no Litestar boundary.

Workflow for designing, querying, and reasoning about databases — schema modeling, normalization, keys/constraints, indexing strategy, query patterns, EXPLAIN plans, transactions and isolation. Covers general database concepts, relational/SQL behavior, engine-specific quirks, non-relational systems, and workload shapes. Defaults to relational; covers non-relational when the user is working there.

Activates BusinessIntelligence-Pro for KPI design, dashboard strategy, and SQL optimization. Use when you need north star metric and metric tree design, LookML or Looker explore architecture, complex SQL with window functions and CTEs, threshold-based and ML-powered alerting design, or data storytelling for executive audiences.

Generate a dev container for my project — auto-detect language, framework, and services like PostgreSQL or Redis, create devcontainer.json with VS Code extensions, port forwarding, post-create commands, Docker Compose for multi-service setups, and GitHub Codespaces compatibility

Activates SQLAnalyzer for advanced SQL optimization, query analysis, and database performance tuning. Use when you need to optimize a slow query using EXPLAIN plans, rewrite subqueries as CTEs or window functions, design complex analytical queries, identify missing indexes, eliminate N+1 patterns, or write advanced SQL using window functions, recursive CTEs, or pivot logic.

Review SQL for business logic correctness, semantic drift, aggregation risk, and silent definition changes.

Validates test quality beyond coverage: uses Claude subagents to generate intelligent mutations for source code, runs them via the project's native test runner (pytest, jest, vitest, mocha, go test), prints a structured summary, generates mutation-todos.md with per-mutant rationale, persists every run to a per-project SQLite ledger and JSONL trace under ./.logbooks/mutation-testing/, and warns whe

Verify database migrations are safe before running them. Checks that migrations apply cleanly, reverse cleanly, preserve data integrity, are idempotent, and will not lock tables or cause downtime on large datasets. Supports Prisma, Knex, Alembic, Django, ActiveRecord, Flyway, TypeORM, Sequelize, and raw SQL. Use when you need to review migrations, check migration safety, validate schema changes, a

Use when adding or reviewing data quality tests for dbt models in warehouse-backed analytics projects. Covers dbt generic tests, singular tests (assert_*.sql), accepted-values macros, dbt_utils patterns, cross-system consistency tests, and warehouse-oriented validation. Use when writing data tests, creating assert_*.sql files, testing business logic, or validating referential integrity.

When the user wants help with revenue operations, lead lifecycle management, or marketing-to-sales handoff processes. Also use when the user mentions 'RevOps,' 'revenue operations,' 'lead scoring,' 'lead routing,' 'MQL,' 'SQL,' 'pipeline stages,' 'deal desk,' 'CRM automation,' 'marketing-to-sales handoff,' 'data hygiene,' 'leads aren't getting to sales,' 'pipeline management,' 'lead qualification,

Use when creating or modifying dimensional dbt models in warehouse-backed analytics projects. Covers a four-layer warehouse architecture (sources/staging/core/marts), naming conventions, no-alias SQL rule, surrogate-key and missing-record patterns, incremental strategies, deduplication, and common project macros. Use when building fact tables, dimension tables, staging models, writing SQL, or desi