New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Prompt Engineer

by shopsys in shopsys/shopsys

Converts user content into a structured prompt using a reusable template.

Custom licenceAuto-check passedAI & LLM Engineering

Install Prompt Engineer

skills CLI
$ npx skills add shopsys/shopsys --skill prompt-engineer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install shopsys/shopsys prompt-engineer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/shopsys/shopsys.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/prompt-engineer .claude/skills/prompt-engineer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
prompt-engineer
GitHub stars
350
Token cost
~616 tokens
SKILL.md length
182 words
Files
1
Skills in repo
38
Repo updated
First seen
Licence
Custom licence

At a glance

Converts user content into a structured prompt using a reusable template.

  • Works in 4 steps: Analyze the provided content - Identify… → Search current session - Look for… → Apply Universal Prompt Template -… → …
  • Tasks that involve Prompt engineering
  • SKILL.md covers Description, Usage, Arguments and Implementation, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Prompt Engineer is an agent skill from shopsys/shopsys. Converts user content into a structured prompt using a reusable template.

Its SKILL.md is about 620 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Prompt engineering. The repository describes itself as: Main repository for maintaining Shopsys Platform packages. Open for ISSUES and PULL REQUESTS.

When your agent uses it

  • Tasks that involve Prompt engineering

Example prompts

  • “Use the prompt-engineer skill to convert user content into a structured prompt using a reusable template”
  • “/prompt-engineer”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Analyze the provided content - Identify domain (technical, business, creative), complexity level, and core requirements
  2. Search current session - Look for relevant context, documents, or previous discussions that add value
  3. Apply Universal Prompt Template - Structure using appropriate template sections based on content analysis
  4. Output complete structured prompt - Ready-to-use prompt following the template format

What it can do on your machine

Read from SKILL.md and the folder at commit 3c4bf38. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Prompt Engineer loads about 616 tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 182 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~22
When it runs · the whole SKILL.md, loaded when a task matches
~616

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 182 words (~616 tokens).

“Converts user content into a well-structured prompt using the Universal Prompt Structure Template. Analyzes session context and formats content for optimal AI interaction.”

— opening of SKILL.md by shopsys, Custom licence
name
prompt-engineer

Read the full SKILL.md on GitHub

Files

Just SKILL.md in .agents/skills/prompt-engineer of shopsys/shopsys.

Open the folder on GitHubat commit 3c4bf38

Compare with similar skills

Prompt Engineer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Prompt Engineer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Prompt Engineer this skillshopsys/shopsys350—~616Automated safety check: PassCustom licence
Prompt Improverseverity1/claude-code-prompt-improver1.9k2 repos~1.7kAutomated safety check: PassMIT
Prompt Engineering Patternsynulihao/AgentSkillOS61715 repos~1.7kAutomated safety check: PassNone
Patch CreationPiebald-AI/tweakcc2.5k—~1.6kAutomated safety check: PassMIT
LLM Application DevMoizIbnYousaf/ai-agent-skills1.1k2 repos~1.3kAutomated safety check: PassMIT
Senior Prompt Engineermaslennikov-ig/claude-code-orchestrator-kit2604 repos~1.4kAutomated safety check: PassCustom licence

Similar skills

  • Prompt Improver

    severity1/claude-code-prompt-improver

    This skill enriches vague prompts with targeted research and clarification before execution.

    1.9k GitHub starsUsed in 2 repos~1.7k tokens
    AI & LLM EngineeringAuto-check passed

  • Prompt Engineering Patterns

    ynulihao/AgentSkillOS

    Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production.

    617 GitHub starsUsed in 15 repos~1.7k tokens
    AI & LLM EngineeringAuto-check passed

  • Patch Creation

    Piebald-AI/tweakcc

    Create and register new patches for tweakcc. An agent skill from Piebald-AI/tweakcc.

    2.5k GitHub stars~1.6k tokensUpdated 2 days ago
    AI & LLM EngineeringAuto-check passed

  • LLM Application Dev

    MoizIbnYousaf/ai-agent-skills

    Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration.

    1.1k GitHub starsUsed in 2 repos~1.3k tokens
    AI & LLM EngineeringAuto-check passed

  • Senior Prompt Engineer

    maslennikov-ig/claude-code-orchestrator-kit

    Provides reference guides and Python scripts for prompt optimization, RAG evaluation, and agent orchestration when building or tuning LLM systems.

    260 GitHub starsUsed in 4 repos~1.4k tokens
    AI & LLM EngineeringAuto-check passed

  • Codex Fable5

    baskduf/FableCodex

    Apply a Claude Fable 5 inspired operating style inside Codex.

    437 GitHub stars~1.6k tokensUpdated 2 mo ago
    AI & LLM EngineeringAuto-check passed

More from shopsys/shopsys

All 38 skills in this repo

  • Adhoc PR

    shopsys/shopsys

    Ad-hoc Pull Request Publisher — commits the current changes, pushes the branch, opens a GitHub pull request against the repository's default branch, and creates a matching SSP Jira issue in the…

    350 GitHub stars~2.3k tokensUpdated yesterday
    Auto-check passed

  • Commit

    shopsys/shopsys

    Interactive commit workflow — analyzes all uncommitted changes, proposes atomic, logically grouped commits with messages following commit-conventions, and executes them only after the user approves…

    350 GitHub stars~771 tokensUpdated yesterday
    Auto-check: notes

  • Create Enum

    shopsys/shopsys

    Create a Shopsys-style enum (a class extending AbstractEnum with public typed constants, NOT a native PHP enum).

    350 GitHub stars~1.9k tokensUpdated yesterday
    Auto-check passed

  • Docs Researcher

    shopsys/shopsys

    Searches and analyzes documentation to provide relevant information for development tasks.

    350 GitHub stars~1.5k tokensUpdated yesterday
    Auto-check passed

  • PR Comments

    shopsys/shopsys

    Work with GitHub PR review threads — list unresolved comments as a digest (who is waiting on whom), reply to threads, and resolve/unresolve them.

    350 GitHub stars~2k tokensUpdated yesterday
    Auto-check passed

  • PR Description

    shopsys/shopsys

    Generates a PR description focused on business value using the project's PR template.

    350 GitHub stars~1.7k tokensUpdated yesterday
    Auto-check passed

Categories

Questions about Prompt Engineer

What does Prompt Engineer do?

Converts user content into a structured prompt using a reusable template. Prompt Engineer is an agent skill from shopsys/shopsys. Converts user content into a structured prompt using a reusable template.

When should I use Prompt Engineer?

Prompt Engineer fits situations like: tasks that involve Prompt engineering.

How do I install Prompt Engineer in Claude Code?

Run `npx skills add shopsys/shopsys --skill prompt-engineer -a claude-code`. Or copy the skill folder (.agents/skills/prompt-engineer in shopsys/shopsys) into .claude/skills/prompt-engineer in your project. Claude Code loads it when a task matches its description.

How do I install Prompt Engineer in Codex?

Run `npx skills add shopsys/shopsys --skill prompt-engineer -a codex`. Or copy the skill folder (.agents/skills/prompt-engineer in shopsys/shopsys) into .agents/skills/prompt-engineer in your project. Codex loads it when a task matches its description.

Can I use Prompt Engineer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add shopsys/shopsys --skill prompt-engineer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/prompt-engineer, .gemini/skills/prompt-engineer, .github/skills/prompt-engineer and .opencode/skills/prompt-engineer in your project.

What does Prompt Engineer need to run?

SKILL.md names no scripts, command-line tools or credentials: Prompt Engineer is instructions for the agent only.

Does Prompt Engineer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Prompt Engineer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Prompt Engineer use?

Prompt Engineer has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Prompt Engineer use?

About 616 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Prompt Engineer?

Skills that share tags, products or a category with Prompt Engineer: Prompt Improver (severity1/claude-code-prompt-improver, 1.9k stars), Prompt Engineering Patterns (ynulihao/AgentSkillOS, 617 stars), Patch Creation (Piebald-AI/tweakcc, 2.5k stars) and LLM Application Dev (MoizIbnYousaf/ai-agent-skills, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Prompt Engineer?

shopsys (a GitHub organization) maintains it in shopsys/shopsys, which has 350 GitHub stars. The repository holds 38 skills in this directory. The repository was last updated on October 7, 2026.

Source: shopsys/shopsys on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.