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Database optimization, query tuning, indexing strategies, migration management, and performance monitoring for PostgreSQL with Drizzle ORM. Use when optimizing slow queries, designing schemas, creating migrations, or setting up database monitoring.
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Use when the user asks about revenue, payments, subscriptions, billing, CRM deals, support tickets, production database tables, or other data that PostHog does not collect natively. Also use when a query fails because a table does not exist or returns no results for expected external data. The data warehouse can import from SaaS tools (Stripe, Hubspot, etc.), production databases (Postgres, MySQL, BigQuery, Snowflake), and other arbitrary data sources. Covers checking existing sources, identifying the right source type, and guiding the setup.
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Guide the user through connecting a new data warehouse source — Postgres, MySQL, Stripe, Hubspot, MongoDB, Salesforce, BigQuery, Snowflake, and so on. Use when the user wants to "connect Stripe", "import data from Postgres", "add a new data source", "sync my warehouse tables", or wants to pick sync methods for each table. Walks through source-type discovery, credential validation, table discovery, per-table sync_type selection, and the final create call. Also covers picking a good prefix and what to do right after creation.
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Investigates a session recording by gathering metadata, person profile, same-session events, and linked error tracking issues in one pass. Use when a user provides a recording or session ID and wants to understand what happened — who the user was, what they did, what errors occurred, and whether there are related error tracking issues. Replaces the manual chain of session-recording-get, persons-retrieve, execute-sql, and query-error-tracking-issues-list.
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ABSOLUTE MUST to debug and inspect LLM/AI agent traces using PostHog's MCP tools. Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly, verify context/files were surfaced, inspect subagent behavior, investigate LLM decisions, or analyze token usage and costs. Also use when raw SQL/HogQL against `events.properties.$ai_input` / `$ai_output_choices` returns empty — message content lives only on the dedicated `posthog.ai_events` table.
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Scrap and regenerate the in-flight EF migrations on the current branch as one consolidated migration. Use when migrations have accumulated mid-development cruft (added/removed columns, stacked add-column-to-existing-table fixes, hand-edited SQL that needs to come out, schema changes that should have been one migration but ended up as five), or when the branch has merged main and its migrations are now stuck mid-chain so `dotnet ef migrations remove` is unsafe. Triggers on phrases like 'regen the migrations', 'redo these migrations', 'scrap and regen migrations', 'consolidate the in-flight migrations', 'redo the migration stack', or any time an agent hits the mid-chain situation in `memory/architecture/migration-regen-after-rebase.md`.
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This skill should be used when users need to work with the DuckDB CLI for querying, analyzing, or transforming data. Use this skill for executing SQL queries, importing/exporting data, configuring DuckDB settings, or performing database operations at the command line.
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Provides expert knowledge of JPA entity design, relationship mapping, Flyway migrations, and PostgreSQL-specific optimizations.
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Generates strictly typed Drizzle ORM schemas for PostgreSQL with indexes, foreign keys, and Zod schema deduction.
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Parses, queries, converts, and extracts from GTF and GFF3 gene-model annotation files - walking the gene/transcript/exon/CDS hierarchy with gffutils (queryable SQLite DB), converting formats and extracting transcript/CDS/protein FASTA with gffread, slurping to dataframes with gtfparse/pyranges, and sanitizing malformed files with AGAT. Covers the 1-based-inclusive vs 0-based BED coordinate conversion (start-1 only), deriving implicit features (introns/UTRs/TSS), phase-not-frame, the stop-codon-in-or-out-of-CDS convention, and the chr1-vs-1 seqid and gene-ID-version mismatches that silently produce all-zero count matrices and dropped joins. Use when extracting features or sequences from an annotation, converting GTF<->GFF3 or GTF->BED, traversing the gene tree, or diagnosing a coordinate/provenance mismatch upstream of counting or DE.
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Use when creating database migrations, schema changes, seed data, or any SQL that modifies database structure. Covers Flyway naming conventions, versioning, and safe migration patterns.
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Guide for building and refactoring a FastAPI + Prefect + PostgreSQL/pgvector analytics pipeline that extracts insights from chat data using LLM classification, embeddings, UMAP/HDBSCAN clustering, and narrative generation. Use this skill whenever working on this project's codebase — including adding features, refactoring, debugging, creating new endpoints, modifying pipeline stages, or reviewing architecture decisions. Also trigger when the user asks about project structure, stack decisions, async migration, or best practices for this specific system.
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Connect to Azure Database for PostgreSQL Flexible Server from Node.js/TypeScript using the pg (node-postgres) package.
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Azure Cosmos DB SDK for Java. NoSQL database operations with global distribution, multi-model support, and reactive patterns.
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Azure Cosmos DB SDK for Rust (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
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Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
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Build production-grade Azure Cosmos DB NoSQL services following clean code, security best practices, and TDD principles.
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Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
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Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.
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Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets.
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Launch and diagnose the required Haloop-routed PostgreSQL FUSE runtime in Openrind Desktop.
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Query PostgreSQL with pg and navigate Openrind Shell's primary FUSE or compatibility workspace; /db is custom-agent-only.
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Develop Openrind Shell's OpenShell-supervised PostgreSQL FUSE runtime, compatibility sync runtime, and just-bash library.
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Use when the user asks about the pwdev-prd audit trail — 'auditoria do prd', 'eventos', 'decisões registradas', 'audit report', 'exportar relatório de auditoria' — querying the shared SQLite database read-only (summary, events, decisions, artifacts, stats, export, query).
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