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Timescaledb

Listed
tukuaiai·vlatest·database·MIT

Timescaledb enables efficient time-series data storage and querying, ideal for applications like monitoring and IoT analytics.

Repository

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Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it skill, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add tradecatlabs/vibe-coding-cn --skill skill -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

tukuaiai

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

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scanned

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Not scanned. none of the 21 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as tukuaiai/vibe-coding-cn.
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About this skill

What it does

This skill provides access to TimeScaleDB functionality within an AI agent. It allows you to interact with and query TimeScaleDB databases, enabling time-series data analysis and management directly through natural language prompts. The skill supports common database operations like creating tables, inserting data, and running complex queries.

When to use it

  • Analyzing sensor data: You have a TimeScaleDB database storing readings from IoT sensors and want the AI agent to identify trends or anomalies.
  • Financial time series analysis: You need to query historical stock prices stored in TimeScaleDB to perform calculations or generate reports.
  • Managing event logs: Your application stores events in TimeScaleDB, and you require the AI agent to extract specific information from these logs based on natural language requests.
  • Building dashboards: You want an AI agent to automatically query data from a TimeScaleDB database and format it for display in a dashboard.

Key capabilities

  • Database interaction (create, read, update, delete)
  • Time-series data querying
  • Data analysis functions
  • Table creation

Example prompts

  • "Create a table called 'temperature_readings' with columns for timestamp and temperature."
  • "What was the average temperature recorded yesterday?"
  • "Insert a new reading into the 'cpu_usage' table: timestamp=now(), value=75.2"

Tips & gotchas

  • Ensure your AI agent has appropriate credentials to access the TimeScaleDB database.
  • TimeScaleDB is optimized for time-series data; complex queries might require understanding of its specific functions and syntax.