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Prompt Optimization Analyzer

Checked
exploration-labs·vlatest·ai-ml

Analyzes prompts to identify areas for improvement, boosting LLM output quality and efficiency.

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 exploration-labs/nates-substack-skills --skill prompt-optimization-analyzer -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

exploration-labs

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 exploration-labs/nates-substack-skills at 61c6afd747.

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

Commit
61c6afd747
Manifest
prompt-optimization-analyzer/SKILL.md
Scanned
1 file, 409 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 Prompt Optimization Analyzer skill evaluates and suggests improvements to prompts used with AI models. It identifies potential issues like ambiguity, lack of clarity, or inefficient phrasing that can hinder the model's ability to generate desired outputs. The analyzer provides specific recommendations for rewriting prompts to enhance performance and achieve more predictable results. This helps users refine their instructions and maximize the effectiveness of AI interactions.

When to use it

  • Improving inconsistent responses: If an AI agent is providing varied or unexpected answers, analyze the prompt to identify areas needing clarification.
  • Reducing token usage: Optimize lengthy prompts to minimize costs associated with API calls by removing unnecessary words or phrases.
  • Debugging complex tasks: When attempting a complicated task that isn't working as expected, use this skill to pinpoint weaknesses in the prompting strategy.
  • Ensuring prompt clarity: Before deploying an AI agent for production use, analyze its prompts to ensure they are unambiguous and lead to consistent results.

Key capabilities

  • Prompt evaluation
  • Suggestion generation
  • Clarity assessment
  • Efficiency analysis

Example prompts

  • "Analyze this prompt: 'Write a short story about a cat.'"
  • "Can you suggest improvements for the following prompt? 'Summarize this article in three sentences.'"
  • "Evaluate and optimize this prompt to reduce token usage: 'Explain the theory of relativity, including its implications for time dilation and gravitational lensing.'"

Tips & gotchas

The skill's effectiveness depends on providing clear and complete prompts. It is designed to analyze text-based prompts; complex instructions involving multiple files or external data sources may yield less accurate results.