Core Data Patterns

Name: Core Data Patterns
Author: kaakati

Checked

kaakati·vlatest·data

Helps with data, patterns as part of agent workflows workflows.

Repository

Install on your platform

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

Run this in your project

terminal

$ npx skills add kaakati/rails-enterprise-dev --skill core-data-patterns -a claude-code

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

kaakati

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 12 Oct 2026

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 kaakati/rails-enterprise-dev at bd0b7c1cc3.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit: bd0b7c1cc3
Manifest: plugins/reactree-ios-dev/skills/core-data-patterns/SKILL.md
Scanned: 2 files, 1,637 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 helps AI agents recognize and apply common data patterns. It enables them to identify recurring structures within datasets, allowing for more efficient analysis and manipulation of information. The agent can use this understanding to extract specific data points or transform the data into a more usable format.

When to use it

Analyzing log files to identify error trends based on repeating sequences of events.
Extracting key information from structured text documents like invoices or reports.
Transforming raw sensor data into meaningful metrics by recognizing patterns in the readings.
Identifying anomalies within a dataset by comparing new entries against established patterns.

Key capabilities

Pattern recognition
Data extraction
Data transformation
Anomaly detection

Example prompts

"Identify repeating sequences of errors in this log file."
"Extract the invoice number and total amount from this document."
"Transform these sensor readings into daily averages."
"Highlight any data points that deviate significantly from the expected pattern."

Tips & gotchas

The effectiveness of this skill depends on the clarity and consistency of the underlying data. Providing well-structured or formatted input will yield better results.