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Prompt Engineering

Listed
sickn33·vlatest·ai-ml·MIT

Crafts optimized prompts for AI models to elicit desired responses, boosting accuracy and effectiveness in your applications.

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 sickn33/agentic-awesome-skills --skill prompt-engineering -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

sickn33

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.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 sickn33/agentic-awesome-skills at c808e6e480.

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

Commit
c808e6e480
Manifest
skills/prompt-engineering/SKILL.md
Scanned
0 files
Copies in repo
3 — all of them scanned
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 enables users to craft and refine prompts for AI agents, ensuring clarity, precision, and effectiveness in interactions. It provides tools to structure queries, define context, and optimize outputs based on specific goals or constraints.

When to use it

  • When you need to generate highly accurate responses from an AI agent by refining your input.
  • To guide the AI toward a particular tone, format, or level of detail in its output.
  • Before deploying an AI agent for a complex task that requires precise instructions.
  • When troubleshooting unclear or inconsistent outputs from an AI agent.

Key capabilities

  • Prompt structuring and optimization
  • Context definition and scenario setup
  • Output formatting control
  • Tone and style customization

Example prompts

  • "Write a detailed explanation of quantum computing in simple terms."
  • "Generate a 500-word blog post about the benefits of renewable energy, using an informative tone."
  • "List five tips for improving productivity at work, formatted as bullet points."

Tips & gotchas

  • Start with clear and specific instructions to avoid ambiguous results.
  • Test variations of your prompt to see how different phrasings affect output quality.