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Tensorpm

Listed
neo552·vlatest·ai-ml

TensorPM helps you monitor and manage your TensorFlow models’ performance metrics, ensuring optimal model health and efficient deployments.

Repository

Install on your platform

This skill no longer installs under the name tensorpm. SKILL.md frontmatter is not valid YAML, so the skills CLI skips it.

We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-20. We don't show a command we know will fail.

Repository install instructions

What we know about this skill

Publisher

neo552

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 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: tensorpm.com.

    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

    tensorpm.comundeclared

    What it found

    • plugins/tensorpm/skills/tensorpm/SKILL.md:24contacts tensorpm.com
      curl -fL -o /tmp/TensorPM-macOS.dmg https://tensorpm.com/api/download/macos
    • plugins/tensorpm/skills/tensorpm/SKILL.md:27contacts tensorpm.com
      curl -fL -o ~/TensorPM.AppImage https://tensorpm.com/api/download/linux
    • plugins/tensorpm/skills/tensorpm/SKILL.md:30contacts tensorpm.com
      Invoke-WebRequest -Uri https://tensorpm.com/api/download/windows -OutFile $env:TEMP\TensorPM-Setup.exe

  • 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 neo552/tensorpm-releases at e6872346ae.

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

Commit
e6872346ae
Manifest
plugins/tensorpm/skills/tensorpm/SKILL.md
Scanned
1 file, 169 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 tensorpm skill provides tools and utilities for managing and manipulating tensors, which are multi-dimensional arrays used in machine learning and scientific computing. It allows agents to perform operations like reshaping, transposing, and calculating statistical properties on tensor data. This skill is designed to streamline workflows involving numerical data processing within AI agent applications.

When to use it

  • Data Preprocessing: Use tensorpm when an agent needs to reshape or normalize input data for a machine learning model.
  • Scientific Simulations: Employ this skill in agents performing simulations that rely on tensor calculations, such as fluid dynamics or molecular modeling.
  • Image Processing: Leverage it for tasks like image resizing, cropping, and feature extraction where tensors represent pixel data.
  • Statistical Analysis: Utilize tensorpm when an agent needs to calculate statistics (mean, variance, etc.) from large datasets represented as tensors.

Key capabilities

  • Tensor reshaping
  • Tensor transposition
  • Calculation of statistical properties on tensors

Example prompts

  • "Reshape this tensor into a 3x4 matrix."
  • "Transpose the following tensor and display the result."
  • "Calculate the mean and standard deviation of this tensor dataset."

Tips & gotchas

The skill's effectiveness depends on the agent having access to properly formatted tensor data. Ensure that input tensors are correctly defined and represent the intended numerical information for accurate processing.