Sql Query Clinic
Diagnose slow or broken SQL: explain plans, index advice, rewrites, and correctness checks.
Skills for databases, data pipelines, ETL, SQL optimization, and data modeling. Handle complex data transformations and schema design.
67 skills
Diagnose slow or broken SQL: explain plans, index advice, rewrites, and correctness checks.
Turn plain English app descriptions into fully normalized SQL schemas and entity relationship documentation.
Automate data profiling with type detection, statistical analysis, and quality flags saved to a Markdown report.
Automatically transform JSON files or raw strings into production-ready TypeScript interfaces or Python dataclasses.
A high-performance scraping engine with Playwright stealth, proxy rotation, and anti-bot bypass capabilities.
Expert Oracle PL/SQL architect for writing, refactoring, and performance-tuning enterprise database logic.
Generates a polite async Python fetch layer with per-domain delays, robots.txt checks, retry backoff, and a generic-mailbox email extractor.
DB type routing, selection decision tree, relational/NoSQL design, performance optimization, 2026 trends.
Production-safe database migrations with zero-downtime strategies, batch backfilling, and multi-ORM support.
Turns plain-English business questions into safe read-only SQL reporting plans, required table/field maps, readable SQL drafts, validation checks, and manager-friendly summaries.
A safe, expert-level database troubleshooter for fixing migrations, performance issues, and schema drift.
Automated Belgian KBO register importer and polite website email enricher for B2B lead generation.
Audit local dbt SQL and YAML for missing model tests, source freshness and test gaps, likely-key coverage, missing model descriptions, SELECT *, and raw table references. Get severity-ranked findings plus starter tests YAML for model/key gaps without running dbt or querying a warehouse.
A 3-step Dutch payment-reminder cadence for an overdue invoice: a friendly nudge, a firm follow-up, and a calm final notice, with a server-side compliance footer and a stop-on-payment rule. Polite where it should be, firm where it must be, never aggressive. Composes on the Nex invoice-bot pattern.
Catch the dangerous migration before it locks or wrecks your production database. Scans SQL migration files for destructive and risky operations: DROP and TRUNCATE, drops without IF EXISTS, lossy column-type changes, NOT NULL added without a default, DELETE or UPDATE with no WHERE, non-concurrent index builds, dropped constraints, renames, and data backfills mixed into schema changes. Each finding is ranked by severity with a safer rewrite. Postgres, MySQL, and SQLite.
Produces a Redis caching design — cacheability assessment, invalidation strategy, TTL and jitter design, and stampede protection for given data patterns. Use when the user says "design our caching layer", "fix cache invalidation", "prevent a thundering herd", "pick a Redis data structure", or "set our cache TTL strategy". Do not use when the request is database schema or index design, not caching.
Produces a full-stack SaaS architecture spec — database schema, authentication, REST API design, multi-tenant patterns, billing, deployment plan — for the stack specified. Use when the user says architect my SaaS, design a database schema for this app, set up authentication and billing, or scaffold a SaaS from spec to production. Do not use when the user wants a single automation pipeline instead.
Manage multiple Postgres versions and extensions on one Linux box with a port registry and unified backups.
Continuously monitor data pipelines, detect anomalies, and explain root causes before failures impact production.
Produces a Postgres schema design — entity modeling, normalization, constraints, index strategy, and multi-tenant isolation choices for a domain. Use when the user says "design my database schema", "review my table design", "how should I index this query", "jsonb vs columns for postgres", or "multi-tenant database design". Do not use when the request is SQL query tuning on an already-fixed schema.
Daily backup-and-restore for a self-hosted Postgres app or Pi: a custom-format pg_dump, app-data tar, config copy, keep-window rotation, and a low-disk Telegram alert, plus a confirm-to-proceed restore, systemd timer, and idempotent install.
Clean messy tabular data with a profile-first workflow, audit logs, and reproducible pandas scripts.
Reviews a database migration for production risk — lock analysis, table-rewrite detection, expand-contract sequencing, backfill batching, rollback plan — for the engine and table size given. Use when the user says review this database migration, is this migration safe for production, will this ALTER TABLE lock the table, or plan a backfill strategy. Do not use for a general code review with no schema changes.
Produces an event taxonomy and tracking plan (naming convention, funnel definitions, data layer spec) derived from the decisions the product needs. Use when the user says "design a GA4 tracking plan", "what events should we track", "build an event naming convention", or "set up Mixpanel events". Do not use when the user wants the analytics dashboard itself, not the tracking plan.
Expert-level SQL tuning and performance auditing for PostgreSQL, MySQL, SQLite, and SQL Server.
Teaches AI coding agents to design safe Prisma schemas that prevent data loss, race conditions, N+1 queries, and the dangerous Prisma migration reset. Covers 12 critical anti-patterns (missing indexes
Catches the database migrations that lock tables or lose data — before they hit production.
Makes your coding agent work like a senior developer: exact money, configurable rules, real audit trails, honest testing. Any stack, any country.
A senior-level B2B lead generation workflow for discovery, enrichment, and multi-signal email verification.
Audit database migrations for production safety, locking risks, and zero-downtime compatibility.
Review schema migrations for lock risk, data loss, backfill cost, and rolling-deploy breakage — get a verdict, safe rewrite, and deploy sequence.
Merge messy spreadsheets using a four-pass deduplication cascade with fuzzy matching and full audit trails.
Architects deterministic, isolated, and privacy-safe test data systems to eliminate flakes and leaks.
Audits spreadsheets for 14 types of data-quality issues and returns an annotated Excel file with highlighted errors.
Generate production-ready PostgreSQL schemas, RLS security policies, and TypeScript types for Supabase projects.
Architects high-fidelity, multi-cloud synthetic datasets for LLM fine-tuning and security auditing.
Repair rounding, floating-point, tax, discount, and total mismatches across existing apps.
Repair long-running exports that produce missing, duplicate, mixed-version, or inconsistent rows when source data changes mid-run.
Repair search indexes that contain missing, stale, duplicated, or deleted records and add safe reconciliation and rebuild controls.
Review annotation guidelines in files the user supplies or is authorized to share.
Repair fragile CSV, JSON, API, and database import scripts so they can be rerun safely.
Repair duplicate writes, oversold inventory, double charges, and other concurrency bugs in APIs.
Consolidates folder-wide spreadsheets into a single file using four-layer semantic and fuzzy deduplication.
Turn raw business data into validated analysis, automated dashboards, insights, and decision-ready reports.
Repair leaked or long-held connections, per-request client pools, fan-out saturation, retry amplification, and cleanup gaps without guessing pool sizes.
Repair transaction boundaries, rollback behavior, nested transaction drift, and unsafe external side effects without widening database locks.
Turn your photos and shopping order screenshots into a structured, searchable JSON wardrobe database with AI vision and automated linting.
Data analysis engine with 4D decision matrix, 15-min quick analysis template, statistics reference, A/B testing playbook, user behavior analysis, SQL templates.
Scraper architecture routing, anti-scraping strategies, data extraction, storage, compliance.
Extracts structured electrical specs, package data, and compliance status from component datasheet PDFs.
Analysis scene routing, Python toolchain, data cleaning SOP, visualization, ML pipeline, 2026 trends.
Plan, review, and execute safe database migrations with automatic rollback plans, backfill strategies, and zero-downtime sequencing.
Governance framework, data quality, metadata, compliance, data lineage, 2026 trends.
Data quality diagnosis, dedup strategies, format standardization, anomaly handling, batch processing.
Review a database schema, queries, or migration for the mistakes that get expensive in production — bad table design, missing or wrong indexes, slow and N+1 queries, SQL injection, and migrations that lock or break prod. Engine-aware (PostgreSQL, MySQL, SQLite, SQL Server), it runs an ordered review and returns a PASS/REVIEW/BLOCK verdict with prioritized fixes. Schema mistakes are the most expensive kind — this catches them before they ship.