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Finalize Agent Prompt

Official
github·vlatest·agents·MIT

Refines agent prompts for clarity, conciseness, and optimal task completion based on best practices.

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 github/awesome-copilot --skill finalize-agent-prompt -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

github

Matched to the vendor's own GitHub organisation.

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 github/awesome-copilot at 6c4d33b9cf.

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

Commit
6c4d33b9cf
Manifest
skills/finalize-agent-prompt/SKILL.md
Scanned
0 files
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 finalize-agent-prompt skill helps users refine and perfect their prompts for AI agents, ensuring clarity, precision, and alignment with intended goals. It provides tools to iterate on prompts, eliminate ambiguity, and optimize them for better performance.

When to use it

  • When you need to ensure your agent understands the task clearly before execution.
  • After initial drafting of a prompt when further refinement is needed.
  • To align complex instructions or multi-step tasks with the AI's capabilities.
  • Before deploying an agent in a production environment for accuracy and reliability.

Key capabilities

  • Iterative prompt refinement based on feedback
  • Ambiguity detection and clarification suggestions
  • Alignment checks between prompt intent and AI capabilities

Example prompts

  • "Refine this prompt to make it clearer: 'Help me with my task.'"
  • "Check if this instruction is unambiguous for the agent: 'Generate a report on climate change.'"
  • "Optimize this prompt for better performance: 'Write an email to a client about project delays.'"

Tips & gotchas

  • Use this skill after drafting your initial prompt, not as a replacement for thoughtful planning.
  • Be specific with your feedback during iterations to get the most accurate refinements.