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Using Timeseries Databases

Listed
ancoleman·vlatest·database·MIT

This skill enables querying and analyzing time-series data stored in specialized databases for insights into trends & patterns over time.

Repository

Install on your platform

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

  1. 1

    Run this in your project

    terminal
    $ npx skills add ancoleman/ai-design-components --skill using-timeseries-databases -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

ancoleman

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.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: packagecloud.io.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    github.comsource hostpackagecloud.ioundeclared

    What it found

    • skills/using-timeseries-databases/references/timescaledb.md:43contacts packagecloud.io
      wget --quiet -O - https://packagecloud.io/timescale/timescaledb/gpgkey | sudo apt-key add -

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned ancoleman/ai-design-components at 76551b7b19.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
76551b7b19
Manifest
skills/using-timeseries-databases/SKILL.md
Scanned
15 files, 5,136 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to interact with and query time series databases. It allows for efficient storage, retrieval, and analysis of data points indexed in time order. The agent can perform aggregations, filtering, and calculations on the stored time series data to generate insights and reports.

When to use it

  • Monitoring System Analysis: Analyze server metrics (CPU usage, memory consumption) over time to identify performance bottlenecks or anomalies.
  • Financial Data Reporting: Generate reports based on historical stock prices, trading volumes, or other financial indicators.
  • IoT Device Telemetry: Process and visualize data streams from IoT devices like sensors or smart appliances.
  • Weather Pattern Analysis: Query weather data to identify trends, predict future conditions, or analyze the impact of climate change.

Key capabilities

  • Querying time series data
  • Data aggregation (e.g., calculating averages, sums)
  • Filtering data based on timestamps and values
  • Performing calculations on time series data

Example prompts

  • "Show me the average CPU usage for server X over the last 24 hours."
  • "What was the closing price of stock Y on January 15th, 2023?"
  • “Calculate the hourly temperature fluctuations in city Z yesterday.”

Tips & gotchas

This skill requires a connection to a configured time series database. The agent's ability to query data depends on the specific syntax and capabilities supported by that database system.