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Anthropic Prompt Engineer

Checked
jamesrochabrun·vlatest·ai-ml·MIT

Crafts highly effective prompts for large language models, maximizing output quality and aligning with desired outcomes.

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 jamesrochabrun/skills --skill anthropic-prompt-engineer -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

jamesrochabrun

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 jamesrochabrun/skills at 2482c17637.

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

Commit
2482c17637
Manifest
skills/anthropic-prompt-engineer/SKILL.md
Scanned
6 files, 1,323 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

The anthropic-prompt-engineer skill optimizes interactions with Anthropic's AI models by structuring complex instructions into clear, actionable formats. It transforms vague user requests into precise prompts that leverage the model's reasoning and context window effectively.

When to use it

  • Refining ambiguous business requirements into detailed project specifications for AI execution.
  • Structuring multi-step logical problems to ensure accurate chain-of-thought reasoning.
  • Enhancing creative writing tasks by defining specific tone, style, and structural constraints.
  • Clarifying technical documentation requests to extract precise code or architectural advice.

Key capabilities

  • Context Optimization: Maximizes the utility of the model's context window for long-form tasks.
  • Instruction Structuring: Converts natural language queries into optimized prompt formats.
  • Reasoning Enhancement: Improves the quality of logical deduction and problem-solving outputs.
  • Constraint Enforcement: Ensures strict adherence to user-defined formatting and stylistic rules.

Example prompts

  • "Use the anthropic-prompt-engineer skill to restructure my vague idea for a marketing campaign into a detailed, step-by-step execution plan."
  • "Apply this skill to convert my rough notes on a software bug into a precise prompt that will help an AI agent debug the issue effectively."
  • "Optimize my request for a Python script using this skill to ensure the generated code includes comprehensive error handling and documentation."

Tips & gotchas

This skill is most effective when your initial input contains some core intent but lacks specific formatting or structural details. While it enhances prompt quality, it does not replace the need for clear foundational context regarding the task's goals.