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Ship Learn Next

Checked
visualxintelligence·vlatest·other·MIT

Analyzes ship designs from images to predict future trends and suggest innovative improvements based on learned patterns.

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 visualxintelligence/agent-toolkit --skill ship-learn-next -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

visualxintelligence

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 visualxintelligence/agent-toolkit at 8e8a9f9711.

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

Commit
8e8a9f9711
Manifest
skills/ship-learn-next/SKILL.md
Scanned
2 files, 497 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

The visualxintelligence-ship-learn-next skill allows AI agents to learn from and adapt based on shipping data. It can analyze shipment details, predict potential delays, and optimize logistics workflows. This enables proactive decision-making and improved operational efficiency within supply chain management.

When to use it

  • Predicting Delivery Times: Use the skill when you need more accurate estimated delivery times for shipments, considering historical data and current conditions.
  • Identifying Potential Delays: Employ this skill to proactively identify potential disruptions in shipping routes or processes that could lead to delays.
  • Optimizing Logistics: Leverage its capabilities to analyze shipment patterns and suggest improvements to logistics workflows.
  • Analyzing Shipment Data: Utilize the skill for deeper insights into shipment performance, identifying areas for cost reduction or efficiency gains.

Key capabilities

  • Shipping data analysis
  • Delay prediction
  • Logistics workflow optimization
  • Adaptation based on historical data

Example prompts

  • "Analyze recent shipping data and predict potential delays in the next week."
  • "Suggest improvements to our current logistics workflow based on shipment performance over the last quarter."
  • "What are the key factors contributing to late deliveries for shipments originating from [location]?"

Tips & gotchas

The skill's accuracy depends heavily on the quality and completeness of the shipping data provided. Ensure that historical data is accurate and up-to-date for optimal performance.