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Found 705 Skills
Cloudflare D1 serverless SQLite on edge. Use for databases, migrations, bindings, or encountering D1_ERROR, statement too long, too many requests queued errors.
Query the ExoPriors Scry API -- SQL-over-HTTPS search across 229M+ entities spanning forums, papers, social media, government records, and prediction markets. Includes cross-platform author identity resolution (actors, people, aliases), OpenAlex academic graph navigation (authors, citations, institutions, concepts), shareable artifacts, and structured agent judgements. Use when the task involves: Scry API, ExoPriors, /v1/scry/query, scry.search, scry.entities, materialized views, corpus search, epistemic infrastructure, 229M entities, lexical search, BM25, structured agent judgements, scry shares, cross-corpus analysis, who is this person, cross-platform identity, OpenAlex, citation graph, coauthor graph, academic papers, author lookup. NOT for: semantic/vector search composition or embedding algebra (use scry-vectors), LLM-based reranking (use scry-rerank), or the user's own local Postgres / non-ExoPriors data sources.
Advanced database design and administration for PostgreSQL, MongoDB, and Redis. Use when designing schemas, optimizing queries, managing database performance, or implementing data patterns.
Production-ready Docker and docker-compose setup for Odoo with PostgreSQL, persistent volumes, environment-based configuration, and Nginx reverse proxy.
This skill should be used when the user asks to "set up Alembic migrations", "create a database migration", "run alembic upgrade", "configure alembic autogenerate", or needs guidance on SQLAlchemy schema versioning and migration best practices.
Convert Dune (Trino) SQL queries to Allium (Snowflake) SQL. SQL dialect conversions (Trino → Snowflake) apply to all chains. Comprehensive Solana and EVM chain mappings included.
Use this skill when designing data warehouses, building star or snowflake schemas, implementing slowly changing dimensions (SCDs), writing analytical SQL for Snowflake or BigQuery, creating fact and dimension tables, or planning ETL/ELT pipelines for analytics. Triggers on dimensional modeling, surrogate keys, conformed dimensions, warehouse architecture, data vault, partitioning strategies, materialized views, and any task requiring OLAP schema design or warehouse query optimization.
Create and manage Codex app automations stored in the local SQLite database (~/.codex/sqlite/codex-dev.db). Use when you need to add, list, update, enable/disable, delete, or run-now automations; edit automation names, prompts, RRULE schedules, or cwd scopes; or inspect automation records while troubleshooting app automation behavior.
Generate database seed scripts with realistic sample data. Reads Drizzle schemas or SQL migrations, respects foreign key ordering, produces idempotent TypeScript or SQL seed files. Handles D1 batch limits, unique constraints, and domain-appropriate data. Use when populating dev/demo/test databases. Triggers: 'seed database', 'seed data', 'sample data', 'populate database', 'db seed', 'test data', 'demo data', 'generate fixtures'.
factory_boy test data generation specialist. Covers Factory, DjangoModelFactory, SQLAlchemyModelFactory, all field declarations (Faker, LazyAttribute, Sequence, SubFactory, RelatedFactory, post_generation, Trait, Maybe, Dict, List), batch creation, pytest integration, and Celery task testing patterns. USE WHEN: user mentions "factory_boy", "test factory", "DjangoModelFactory", "SQLAlchemyModelFactory", asks about "test data generation", "factory traits", "SubFactory", "factory fixtures". DO NOT USE FOR: pytest internals - use `pytest`; Django setup - use `pytest-django`; Hypothesis property testing - use `pytest` with Hypothesis
Build with Firestore NoSQL database - real-time sync, offline support, and scalable document storage. Use when: creating collections, querying documents, setting up security rules, handling real-time listeners, or troubleshooting permission-denied, quota exceeded, invalid query, or offline persistence errors. Prevents 10 documented errors.
TimescaleDB - PostgreSQL extension for high-performance time-series and event data analytics, hypertables, continuous aggregates, compression, and real-time analytics