timescaledb
About
This skill provides comprehensive assistance for TimescaleDB development, helping developers implement and debug time-series solutions. It covers key features like hypertables, continuous aggregates, compression, and real-time analytics. Use it when working with TimescaleDB features, APIs, or implementing best practices for time-series data.
Documentation
Timescaledb Skill
Comprehensive assistance with timescaledb development, generated from official documentation.
When to Use This Skill
This skill should be triggered when:
- Working with timescaledb
- Asking about timescaledb features or APIs
- Implementing timescaledb solutions
- Debugging timescaledb code
- Learning timescaledb best practices
Quick Reference
Common Patterns
Quick reference patterns will be added as you use the skill.
Example Code Patterns
Example 1 (bash):
rails new my_app -d=postgresql
cd my_app
Example 2 (ruby):
gem 'timescaledb'
Example 3 (shell):
kubectl create namespace timescale
Example 4 (shell):
kubectl config set-context --current --namespace=timescale
Example 5 (sql):
DROP EXTENSION timescaledb;
Reference Files
This skill includes comprehensive documentation in references/:
- api.md - Api documentation
- compression.md - Compression documentation
- continuous_aggregates.md - Continuous Aggregates documentation
- getting_started.md - Getting Started documentation
- hyperfunctions.md - Hyperfunctions documentation
- hypertables.md - Hypertables documentation
- installation.md - Installation documentation
- other.md - Other documentation
- performance.md - Performance documentation
- time_buckets.md - Time Buckets documentation
- tutorials.md - Tutorials documentation
Use view to read specific reference files when detailed information is needed.
Working with This Skill
For Beginners
Start with the getting_started or tutorials reference files for foundational concepts.
For Specific Features
Use the appropriate category reference file (api, guides, etc.) for detailed information.
For Code Examples
The quick reference section above contains common patterns extracted from the official docs.
Resources
references/
Organized documentation extracted from official sources. These files contain:
- Detailed explanations
- Code examples with language annotations
- Links to original documentation
- Table of contents for quick navigation
scripts/
Add helper scripts here for common automation tasks.
assets/
Add templates, boilerplate, or example projects here.
Notes
- This skill was automatically generated from official documentation
- Reference files preserve the structure and examples from source docs
- Code examples include language detection for better syntax highlighting
- Quick reference patterns are extracted from common usage examples in the docs
Updating
To refresh this skill with updated documentation:
- Re-run the scraper with the same configuration
- The skill will be rebuilt with the latest information
Quick Install
/plugin add https://github.com/2025Emma/vibe-coding-cn/tree/main/timescaledbCopy and paste this command in Claude Code to install this skill
GitHub 仓库
Related Skills
csv-data-summarizer
MetaThis skill automatically analyzes CSV files to generate comprehensive statistical summaries and visualizations using Python's pandas and matplotlib/seaborn. It should be triggered whenever a user uploads or references CSV data without prompting for analysis preferences. The tool provides immediate insights into data structure, quality, and patterns through automated analysis and visualization.
llamaindex
MetaLlamaIndex is a data framework for building RAG-powered LLM applications, specializing in document ingestion, indexing, and querying. It provides key features like vector indices, query engines, and agents, and supports over 300 data connectors. Use it for document Q&A, chatbots, and knowledge retrieval when building data-centric applications.
hybrid-cloud-networking
MetaThis skill configures secure hybrid cloud networking between on-premises infrastructure and cloud platforms like AWS, Azure, and GCP. Use it when connecting data centers to the cloud, building hybrid architectures, or implementing secure cross-premises connectivity. It supports key capabilities such as VPNs and dedicated connections like AWS Direct Connect for high-performance, reliable setups.
Excel Analysis
MetaThis skill enables developers to analyze Excel files and perform data operations using pandas. It can read spreadsheets, create pivot tables, generate charts, and conduct data analysis on .xlsx files and tabular data. Use it when working with Excel files, spreadsheets, or any structured tabular data within Claude Code.
