Skip to content
TrustedSkillsbeta
Back to all skills

Linear

Official
openai·vlatest·ai-ml

Generates creative text formats like poems, code, scripts, musical pieces, email, letters, etc., based on a single prompt – useful for diverse content creation needs.

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 openai/skills --skill linear -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

openai

Matched to the vendor's own GitHub organisation.

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: mcp.linear.app.

    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

    mcp.linear.appundeclared

    What it found

    • skills/.curated/linear/agents/openai.yaml:14contacts mcp.linear.app
      url: "https://mcp.linear.app/mcp"

  • 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 openai/skills at 49f948faa9.

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

Commit
49f948faa9
Manifest
skills/.curated/linear/SKILL.md
Scanned
3 files, 101 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 linear skill enables AI agents to perform tasks that involve linear algebra operations, such as solving systems of equations, matrix manipulation, and vector calculations. It is particularly useful in fields like data science, machine learning, and engineering where mathematical computations are essential.

When to use it

  • Solving a system of linear equations for optimization problems
  • Performing matrix inversion or decomposition for statistical analysis
  • Calculating dot products or cross products in physics simulations

Key capabilities

  • Matrix multiplication and inversion
  • Vector operations (addition, subtraction, dot product)
  • Solving systems of linear equations
  • Eigenvalue and eigenvector computation

Example prompts

  • "Solve the system of equations: 2x + 3y = 5 and x - y = 1."
  • "Calculate the inverse of the matrix [[4, 7], [2, 6]]."
  • "Find the eigenvalues and eigenvectors of the matrix [[3, -1], [2, 0]]."

Tips & gotchas

  • Ensure input data is in a valid numerical format for accurate computation.
  • Some operations may be computationally intensive with large matrices; consider performance implications.