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Eval Core Scorecard

Checked
whitespectre·vlatest·ai-ml

Evaluates a core system’s performance against a predefined scorecard, identifying key strengths and weaknesses for targeted 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 whitespectre/ai-assistant-evals --skill eval-core-scorecard -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

whitespectre

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 whitespectre/ai-assistant-evals at 8d48470982.

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

Commit
8d48470982
Manifest
skills/eval-core-scorecard/SKILL.md
Scanned
2 files, 64 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 eval-core-scorecard skill provides a structured framework for evaluating AI assistant responses. It generates a scorecard based on predefined criteria, assigning scores and providing justifications for each evaluation point. This allows for consistent and objective assessment of AI agent performance across various tasks and prompts.

When to use it

  • Benchmarking: Compare the performance of different AI agents or models on specific tasks.
  • Prompt Engineering Iteration: Evaluate how changes to your prompts impact an AI's output quality.
  • Training Data Assessment: Analyze the effectiveness of training data by assessing agent responses to representative examples.
  • Identifying Weaknesses: Pinpoint areas where an AI assistant struggles and requires further improvement.

Key capabilities

  • Scorecard generation based on predefined criteria
  • Automated scoring and justification
  • Evaluation across various dimensions (e.g., accuracy, relevance, helpfulness)
  • Consistent assessment framework

Example prompts

  • "Evaluate the following response: [AI Response] using the core scorecard."
  • "Score this AI assistant's answer to the prompt '[Prompt]' and provide justifications for each score."
  • "Generate a scorecard for this conversation between a user and an AI agent: [Conversation Transcript]"

Tips & gotchas

The effectiveness of the skill depends on the quality and relevance of the predefined evaluation criteria. Ensure these criteria are aligned with your specific assessment goals for accurate and meaningful results.