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Nemo Evaluator

Checked
eyadsibai·vlatest·other

Nemo Evaluator assesses the quality of generated text based on a defined prompt, ensuring outputs align with desired criteria and improving consistency.

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 eyadsibai/ltk --skill nemo-evaluator -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

eyadsibai

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 eyadsibai/ltk at f8e85697b9.

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

Commit
f8e85697b9
Manifest
plugins/ltk-data/skills/nemo-evaluator/SKILL.md
Scanned
1 file, 184 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 nemo-evaluator skill provides a way to evaluate text generation models using NVIDIA's NeMo framework. It allows you to run inference on specified models and assess their performance based on predefined metrics. This facilitates the comparison of different model outputs and helps in identifying areas for improvement during development or deployment.

When to use it

  • Model Comparison: Evaluate multiple text generation models (e.g., summarization, translation) against each other to determine which performs best for a given task.
  • Performance Monitoring: Track the performance of a deployed model over time and identify potential degradation in quality.
  • A/B Testing: Compare different versions of a model or prompting strategies to optimize output quality.
  • Automated Evaluation Pipelines: Integrate into automated workflows for continuous model evaluation and improvement.

Key capabilities

  • Model inference using NVIDIA NeMo
  • Performance metric calculation
  • Comparison of model outputs
  • Integration with automated pipelines

Example prompts

  • "Evaluate the summarization performance of Model A versus Model B on this dataset."
  • "Run inference with the 'translation' model and calculate BLEU score."
  • "Compare the output quality of these two models using ROUGE metrics."

Tips & gotchas

  • Requires NVIDIA NeMo to be installed and configured.
  • Ensure that the specified models are compatible with the nemo-evaluator skill's supported architectures.