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Found 58 Skills
Diagnose and resolve ClickHouse grant and authentication errors, especially after upgrades. Use when queries fail with ACCESS_DENIED/NOT_ENOUGH_PRIVILEGES, AUTHENTICATION_FAILED/WRONG_PASSWORD/REQUIRED_PASSWORD, or ON CLUSTER privilege errors; when system.* or INFORMATION_SCHEMA access is denied; or when grant behavior changes after version upgrades.
Diagnose ClickHouse RAM usage, OOM errors, memory pressure, and allocation patterns. Use for memory-related issues and out-of-memory errors.
ClickHouse cluster migration planner. Use when planning data migration between ClickHouse clusters, including cross-cluster migrations, horizontal scaling, disk downgrade, availability zone changes, or migrating from self-built/non-Alibaba Cloud ClickHouse to Alibaba Cloud ClickHouse (Community or Enterprise Edition). Helps analyze migration conditions, select appropriate migration methods, and generate detailed migration plans.
Run ClickHouse queries for analytics, metrics analysis, and event data exploration. Use when you need to query ClickHouse directly, analyze metrics, check event tracking data, or test query performance. Read-only by default.
Sets up and manages Postgres using the clickhousectl CLI — runs a local Docker-backed Postgres for development, and creates and operates managed ClickHouse Cloud Postgres services (connections, TLS, runtime config, read replicas, failover, point-in-time restore). Use when the user wants a Postgres or PostgreSQL database for their application, a local Postgres dev environment, psql access, or a managed/production Postgres in ClickHouse Cloud, or mentions moving a local Postgres to production.
Runs a quick overview of Clickhouse server health.
Enterprise AI adoption platform for Claude Code — measures team usage via OpenTelemetry, syncs skills/MCP servers/hooks from a central dashboard, and delivers context-aware skill suggestions at prompt time. Solves the Intention-Action Gap: organizations that deploy Zeude see 3x adoption improvement (6% → 18%). Requires Supabase (config) and ClickHouse (analytics). Triggers on: zeude, ai adoption, claude code adoption, enterprise claude, opentelemetry claude, skill sync, team claude management.
Write raw ClickHouse SQL for a SigNoz dashboard panel — timeseries, value, or table widgets that the builder UI cannot express (custom joins, window functions, regex extraction over log bodies, aggregations beyond builder syntax). Trigger when the user explicitly asks for a "ClickHouse query", a "raw SQL panel", a "custom SQL widget", or describes a SigNoz dashboard panel whose query needs SQL the builder cannot produce. Anchored to dashboard-panel SQL specifically. For ad-hoc data exploration that does not need to land in a panel, use `signoz-generating-queries` instead.
Sets up and manages ClickHouse using the clickhousectl CLI — installs and runs a local ClickHouse server for development, and creates managed ClickHouse Cloud services for production (authentication, service creation, schema migration, application connection). Use when the user wants to build an application with ClickHouse, set up a local ClickHouse dev environment, create tables and start querying, deploy ClickHouse to production or ClickHouse Cloud, or migrate from a local setup to the cloud.
Drop-in pandas replacement with ClickHouse performance. Use `import chdb.datastore as pd` (or `from datastore import DataStore`) and write standard pandas code — same API, 10-100x faster on large datasets. Supports 16+ data sources (MySQL, PostgreSQL, S3, MongoDB, ClickHouse, Iceberg, Delta Lake, etc.) and 10+ file formats (Parquet, CSV, JSON, Arrow, ORC, etc.) with cross-source joins. Use this skill when the user wants to analyze data with pandas-style syntax, speed up slow pandas code, query remote databases or cloud storage as DataFrames, or join data across different sources — even if they don't explicitly mention chdb or DataStore. Do NOT use for raw SQL queries, ClickHouse server administration, or non-Python languages.
Time-series database implementation for metrics, IoT, financial data, and observability backends. Use when building dashboards, monitoring systems, IoT platforms, or financial applications. Covers TimescaleDB (PostgreSQL), InfluxDB, ClickHouse, QuestDB, continuous aggregates, downsampling (LTTB), and retention policies.
Use this skill when a user wants to store, manage, or work with Goldsky secrets — the named credential objects used by pipeline sinks. This includes: creating a new secret from a connection string or credentials, listing or inspecting existing secrets, updating or rotating credentials after a password change, and deleting secrets that are no longer needed. Trigger for any query where the user mentions 'goldsky secret', wants to securely store database credentials for a pipeline, or is working with sink authentication for PostgreSQL, Neon, Supabase, ClickHouse, Kafka, S3, Elasticsearch, DynamoDB, SQS, OpenSearch, or webhooks.