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Pattern Learning

Checked
bejranonda·vlatest·ai-ml

This skill enables the AI to recognize and replicate patterns in data, boosting its ability to predict outcomes and generate similar content effectively.

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 bejranonda/llm-autonomous-agent-plugin-for-claude --skill pattern-learning -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

bejranonda

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 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 bejranonda/llm-autonomous-agent-plugin-for-claude at d7c47f644e.

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

Commit
d7c47f644e
Manifest
skills/pattern-learning/SKILL.md
Scanned
1 file, 485 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 allows an AI agent to identify and learn from patterns in data. It can analyze sequences of events, user actions, or other structured information to predict future outcomes or adapt its behavior accordingly. The agent can then use these learned patterns to make more informed decisions and automate tasks that require recognizing recurring trends.

When to use it

  • Predicting User Behavior: Anticipate what a user might do next based on their past actions within an application.
  • Automating Repetitive Tasks: Identify sequences of steps needed for a common task, then automate the entire process once the pattern is learned.
  • Detecting Anomalies: Recognize deviations from established patterns to flag potential errors or security threats.
  • Optimizing Processes: Learn optimal workflows by analyzing successful and unsuccessful attempts at completing a particular goal.

Key capabilities

  • Pattern identification
  • Sequence analysis
  • Predictive modeling
  • Behavior adaptation

Example prompts

  • "Analyze the user's clickstream data to predict their next action."
  • "Learn the steps required to process an order and then automate it for future orders."
  • "Identify any unusual patterns in server logs that might indicate a security breach."

Tips & gotchas

The agent needs sufficient training data (examples of sequences) to effectively learn patterns. The quality and relevance of this data are crucial for accurate predictions and reliable automation.