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Skill Test

Listed
databricks-solutions·vlatest·testing

Evaluates AI model performance on custom datasets to identify strengths, weaknesses, and areas for improvement.

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 databricks-solutions/ai-dev-kit --skill skill-test -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

databricks-solutions

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 2 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: adb-123456789.11.azuredatabricks.net, docs.databricks.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

    adb-123456789.11.azuredatabricks.netundeclareddocs.databricks.comundeclared

    What it found (3 of 5)

    • .test/skills/databricks-config/ground_truth.yaml:27contacts adb-123456789.11.azuredatabricks.net
      host       = https://adb-123456789.11.azuredatabricks.net/
    • .test/skills/databricks-config/ground_truth.yaml:67contacts adb-123456789.11.azuredatabricks.net
      host                  = https://adb-123456789.11.azuredatabricks.net/
    • .test/skills/databricks-config/ground_truth.yaml:141contacts adb-123456789.11.azuredatabricks.net
      host       = https://adb-123456789.11.azuredatabricks.net/

  • 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 databricks-solutions/ai-dev-kit at b059fd017a.

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

Commit
b059fd017a
Manifest
.test/SKILL.md
Scanned
60 files, 10,436 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

This skill, skill-test, provides a mechanism for testing and validating AI agent functionality. It allows users to execute predefined tests against an agent and receive feedback on its performance. The purpose is to ensure agents meet specific criteria or benchmarks before deployment.

When to use it

  • Automated Regression Testing: Regularly assess an agent's core capabilities after updates or modifications.
  • New Agent Evaluation: Quickly determine if a newly developed AI agent meets minimum performance standards.
  • Integration Testing: Verify that different components of an AI system work together as expected.
  • Performance Benchmarking: Compare the performance of multiple agents against standardized tests.

Key capabilities

  • Test execution
  • Feedback reporting
  • Predefined test cases
  • Performance assessment

Example prompts

  • "Run the 'basic_functionality' test suite."
  • "Execute the integration tests and report any failures."
  • "Can you perform a regression test on the agent?"

Tips & gotchas

The skill requires a properly configured testing environment to function correctly. Ensure that all dependencies are met before attempting to run tests; otherwise, errors may occur during execution.