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Python Sdk

Checked
comet-ml·vlatest·backend·Apache-2.0

Helps with machine learning, Python as part of developing backend services and APIs workflows.

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 comet-ml/opik --skill python-sdk -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

comet-ml

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 comet-ml/opik at 7948263f97.

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

Commit
7948263f97
Manifest
.agents/skills/python-sdk/SKILL.md
Scanned
5 files, 560 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 comet-ml-python-sdk skill provides programmatic access to Comet.ml's experiment tracking and model management platform through the Python SDK. It allows agents to log parameters, metrics, artifacts (like models), and other data associated with machine learning experiments. This facilitates reproducibility, collaboration, and analysis of ML workflows.

When to use it

  • Automated Experiment Tracking: Integrate Comet.ml into an automated training pipeline to automatically track experiment results without manual intervention.
  • Model Versioning & Management: Log model versions and associated metadata for easy retrieval and deployment.
  • Debugging & Analysis: Analyze past experiments by accessing logged parameters, metrics, and artifacts to identify areas for improvement.
  • Reproducibility: Ensure that machine learning experiments are fully reproducible by capturing all relevant information in Comet.ml.

Key capabilities

  • Experiment tracking
  • Parameter logging
  • Metric logging
  • Artifact (model) logging
  • Model versioning

Example prompts

  • "Log the current training epoch and loss value to Comet.ml."
  • "Upload the trained model my_model.pth as an artifact to the experiment in Comet.ml."
  • "Record the learning rate and batch size used for this training run with Comet.ml."

Tips & gotchas

The agent needs access to a valid Comet.ml API key to use this skill effectively. Ensure the environment is properly configured with the comet_ml Python package installed before attempting to utilize its features.