timescaledb
TimescaleDB - PostgreSQL extension for high-performance time-series and event data analytics, hypertables, continuous aggregates, compression, and real-time analytics
What this skill does
# 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):
```bash
rails new my_app -d=postgresql
cd my_app
```
**Example 2** (ruby):
```ruby
gem 'timescaledb'
```
**Example 3** (shell):
```shell
kubectl create namespace timescale
```
**Example 4** (shell):
```shell
kubectl config set-context --current --namespace=timescale
```
**Example 5** (sql):
```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:
1. Re-run the scraper with the same configuration
2. The skill will be rebuilt with the latest information
Related in Data & Analytics
clawarr-suite
IncludedComprehensive management for self-hosted media stacks (Sonarr, Radarr, Lidarr, Readarr, Prowlarr, Bazarr, Overseerr, Plex, Tautulli, SABnzbd, Recyclarr, Unpackerr, Notifiarr, Maintainerr, Kometa, FlareSolverr). Deep library exploration, analytics, dashboard generation, content management, request handling, subtitle management, indexer control, download monitoring, quality profile sync, library cleanup automation, notification routing, collection/overlay management, and media tracker integration (Trakt, Letterboxd, Simkl).
querying-soql
IncludedSOQL query generation, optimization, and analysis with 100-point scoring. Use this skill when the user needs SOQL/SOSL authoring or optimization: natural-language-to-query generation, relationship queries, aggregates, query-plan analysis, and performance or safety improvements for Salesforce queries. TRIGGER when: user writes, optimizes, or debugs SOQL/SOSL queries, touches .soql files, or asks about relationship queries, aggregates, or query performance. DO NOT TRIGGER when: bulk data operations (use handling-sf-data), Apex DML logic (use generating-apex), or report/dashboard queries.
app-store-optimization
IncludedApp Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.
habit-flow
IncludedAI-powered atomic habit tracker with natural language logging, streak tracking, smart reminders, and coaching. Use for creating habits, logging completions naturally ("I meditated today"), viewing progress, and getting personalized coaching.
app-store-optimization
IncludedApp Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.
visualizing-data
IncludedBuilds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.