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Performance Benchmark Setter

Checked
archive-dot-com·vlatest·ai-ml

Automatically establishes baseline performance metrics for AI models based on historical data and industry standards.

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 archive-dot-com/creator-marketing-skills --skill performance-benchmark-setter -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

archive-dot-com

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 archive-dot-com/creator-marketing-skills at ecaf7cf795.

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

Commit
ecaf7cf795
Manifest
skills/performance-benchmark-setter/SKILL.md
Scanned
1 file, 334 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 allows AI agents to establish performance benchmarks for various tasks. It can define metrics, set target values, and track progress against those targets. The agent uses these benchmarks to optimize its output and ensure consistent quality over time.

When to use it

  • Content Creation: Set a benchmark for article word count or video length to maintain consistency across multiple pieces of content.
  • Code Generation: Establish a performance target (e.g., code execution speed) to guide the AI agent's coding process.
  • Data Analysis: Define accuracy thresholds when analyzing data sets, ensuring reliable results.
  • Customer Service Chatbots: Measure and improve response time or customer satisfaction scores over time.

Key capabilities

  • Metric definition
  • Target value setting
  • Progress tracking
  • Performance optimization

Example prompts

  • "Set a benchmark for generating blog posts, aiming for 1500 words per post."
  • "Establish a performance target of 95% accuracy when classifying customer support tickets."
  • "Track the average response time for chatbot interactions and set a goal to reduce it by 20%."

Tips & gotchas

The skill's effectiveness relies on clearly defined metrics. Ensure you provide specific, measurable criteria for the AI agent to track.