Greptimedb Pipeline
CheckedAutomates database schema changes & deployments across environments using GitOps principles for reliable DevOps pipelines.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add greptimeteam/docs --skill greptimedb-pipeline -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
greptimeteam
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.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
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 undeclared network calls: passed
Makes no network calls.
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.
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 greptimeteam/docs at c3b0c72237.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- c3b0c72237
- Scanned
- 1 file, 181 lines
About this skill
What it does
The greptimedb-pipeline skill automates data extraction and analysis from time series databases. It allows users to query, filter, and aggregate data based on specific criteria, then output the results in a structured format suitable for further processing or reporting. This pipeline is designed to streamline DevOps workflows involving database monitoring and anomaly detection.
When to use it
- Automated Reporting: Generate regular reports summarizing key performance indicators (KPIs) extracted from time series data.
- Anomaly Detection: Identify unusual patterns in database metrics, triggering alerts or automated remediation actions.
- Performance Troubleshooting: Quickly diagnose performance bottlenecks by querying and analyzing relevant database logs and statistics.
- Capacity Planning: Forecast future resource needs based on historical trends observed in time series data.
Key capabilities
- Time series database querying
- Data filtering and aggregation
- Structured output formatting
- Automated pipeline execution
Example prompts
- "Extract the average CPU utilization from the database over the last 24 hours."
- "Show me all error logs from the database that occurred in the past week, sorted by severity."
- "Generate a report summarizing the number of active connections to the database each hour today."
Tips & gotchas
The skill requires access credentials and connection details for the target time series database. Ensure these are provided securely and accurately within the prompt or environment variables.