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Found 788 Skills
Reduce an unoptimized-query-oracle test failure log to the simplest possible reproduction case. Use when you have unoptimized-query-oracle*.log files from a failed roachtest and need to find the minimal SQL to reproduce the bug.
SQL query patterns, schema design, and optimization. Joins, CTEs, window functions, indexing, and anti-patterns. Use when writing SQL queries, designing schemas, optimizing database performance, or reviewing database code.
End-to-end pipeline to extract, decrypt, and visualize WeChat Mac favorites from encrypted SQLite DB into an interactive HTML report.
Generate a test suite of natural-language → SQL pairs that becomes the quality benchmark for a nao agent, then run it via `nao test`. Use when the user wants to start measuring agent reliability, extend an existing test suite, or add tests for new metrics. Tests are the only honest answer to "is the context working?". Do not use for writing rules (write-context-rules) or diagnosing failures (audit-context).
Oracle Database skills for administration, SQL and PL/SQL development, performance tuning, security, ORDS, SQLcl, migrations, frameworks, Oracle Container Registry guidance, and agent-safe database workflows.
The apartment-hunt CLI that actually works in 2026 — Surf-cleared bot protection plus a local SQLite store the website itself doesn't have. Trigger phrases: `find apartments in <city>`, `watch apartment listings for <area>`, `rank rentals by price per square foot`, `compare these apartments`, `use apartments-pp-cli`, `run apartments`.
Salesforce Data Cloud Segment phase. Use this skill when the user creates or publishes segments, manages calculated insights, or troubleshoots audience SQL in Data Cloud. TRIGGER when: user creates or publishes segments, manages calculated insights, inspects segment counts or membership, or troubleshoots audience SQL in Data Cloud. DO NOT TRIGGER when: the task is DMO/mapping/identity-resolution work (use harmonizing-datacloud), activation work (use activating-datacloud), query/search-index work (use retrieving-datacloud), or Standard Data Model (STDM)/session tracing (use observing-agentforce).
Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces). Covers HogQL syntax differences from ClickHouse SQL, system table schemas (system.*), available functions, query examples, and the schema-discovery workflow.
Connect to Postgres databases, run SQL and diagnostics, inspect schemas and migrations, review query performance, and use common PostGIS or pgvector patterns.
Translates natural language data intents into syntactically valid Perfetto SQL queries and executes them against a local trace file. Use this skill to extract slice, thread, or memory data from Android Perfetto traces using trace_processor.
End-to-end data engineering pipeline using Harvard Art Museums API with ETL, SQL analytics, and Streamlit visualization
ETL pipeline and analytics application for Harvard Art Museums API with SQL storage and Streamlit visualization