#601

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command-creator AI Agent Skill

Quellcode ansehen: cachemoney/agent-toolkit

Safe

Installation

npx skills add cachemoney/agent-toolkit --skill command-creator

6

Installationen

Command Creator

This skill guides the creation of Claude Code slash commands - reusable workflows that can be invoked with /command-name in Claude Code conversations.

About Slash Commands

Slash commands are markdown files stored in .claude/commands/ (project-level) or ~/.claude/commands/ (global/user-level) that get expanded into prompts when invoked. They're ideal for:

  • Repetitive workflows (code review, PR submission, CI fixing)
  • Multi-step processes that need consistency
  • Agent delegation patterns
  • Project-specific automation

When to Use This Skill

Invoke this skill when users:

  • Ask to "create a command" or "make a slash command"
  • Want to automate a repetitive workflow
  • Need to document a consistent process for reuse
  • Say "I keep doing X, can we make a command for it?"
  • Want to create project-specific or global commands

Bundled Resources

This skill includes reference documentation for detailed guidance:

  • references/patterns.md - Command patterns (workflow automation, iterative fixing, agent delegation, simple execution)
  • references/examples.md - Real command examples with full source (submit-stack, ensure-ci, create-implementation-plan)
  • references/best-practices.md - Quality checklist, common pitfalls, writing guidelines, template structure

Load these references as needed when creating commands to understand patterns, see examples, or ensure quality.

Command Structure Overview

Every slash command is a markdown file with:

---
description: Brief description shown in /help (required)
argument-hint: <placeholder> (optional, if command takes arguments)
---

# Command Title

[Detailed instructions for the agent to execute autonomously]

Command Creation Workflow

Step 1: Determine Location

Auto-detect the appropriate location:

  1. Check git repository status: git rev-parse --is-inside-work-tree 2>/dev/null
  2. Default location:
    • If in git repo → Project-level: .claude/commands/
    • If not in git repo → Global: ~/.claude/commands/
  3. Allow user override:
    • If user explicitly mentions "global" or "user-level" → Use ~/.claude/commands/
    • If user explicitly mentions "project" or "project-level" → Use .claude/commands/

Report the chosen location to the user before proceeding.

Step 2: Show Command Patterns

Help the user understand different command types. Load references/patterns.md to see available patterns:

  • Workflow Automation - Analyze → Act → Report (e.g., submit-stack)
  • Iterative Fixing - Run → Parse → Fix → Repeat (e.g., ensure-ci)
  • Agent Delegation - Context → Delegate → Iterate (e.g., create-implementation-plan)
  • Simple Execution - Run command with args (e.g., codex-review)

Ask the user: "Which pattern is closest to what you want to create?" This helps frame the conversation.

Step 3: Gather Command Information

Ask the user for key information:

A. Command Name and Purpose

Ask:

  • "What should the command be called?" (for filename)
  • "What does this command do?" (for description field)

Guidelines:

  • Command names MUST be kebab-case (hyphens, NOT underscores)
    • ✅ CORRECT: submit-stack, ensure-ci, create-from-plan
    • ❌ WRONG: submit_stack, ensure_ci, create_from_plan
  • File names match command names: my-command.md → invoked as /my-command
  • Description should be concise, action-oriented (appears in /help output)

B. Arguments

Ask:

  • "Does this command take any arguments?"
  • "Are arguments required or optional?"
  • "What should arguments represent?"

If command takes arguments:

  • Add argument-hint: <placeholder> to frontmatter
  • Use <angle-brackets> for required arguments
  • Use [square-brackets] for optional arguments

C. Workflow Steps

Ask:

  • "What are the specific steps this command should follow?"
  • "What order should they happen in?"
  • "What tools or commands should be used?"

Gather details about:

  • Initial analysis or checks to perform
  • Main actions to take
  • How to handle results
  • Success criteria
  • Error handling approach

D. Tool Restrictions and Guidance

Ask:

  • "Should this command use any specific agents or tools?"
  • "Are there any tools or operations it should avoid?"
  • "Should it read any specific files for context?"

Step 4: Generate Optimized Command

Create the command file with agent-optimized instructions. Load references/best-practices.md for:

  • Template structure
  • Best practices for agent execution
  • Writing style guidelines
  • Quality checklist

Key principles:

  • Use imperative/infinitive form (verb-first instructions)
  • Be explicit and specific
  • Include expected outcomes
  • Provide concrete examples
  • Define clear error handling

Step 5: Create the Command File

  1. Determine full file path:

    • Project: .claude/commands/[command-name].md
    • Global: ~/.claude/commands/[command-name].md
  2. Ensure directory exists:

    mkdir -p [directory-path]
  3. Write the command file using the Write tool

  4. Confirm with user:

    • Report the file location
    • Summarize what the command does
    • Explain how to use it: /command-name [arguments]

Step 6: Test and Iterate (Optional)

If the user wants to test:

  1. Suggest testing: You can test this command by running: /command-name [arguments]
  2. Be ready to iterate based on feedback
  3. Update the file with improvements as needed

Quick Tips

For detailed guidance, load the bundled references:

  • Load references/patterns.md when designing the command workflow
  • Load references/examples.md to see how existing commands are structured
  • Load references/best-practices.md before finalizing to ensure quality

Common patterns to remember:

  • Use Bash tool for pytest, pyright, ruff, prettier, make, gt commands
  • Use Task tool to invoke subagents for specialized tasks
  • Check for specific files first (e.g., .PLAN.md) before proceeding
  • Mark todos complete immediately, not in batches
  • Include explicit error handling instructions
  • Define clear success criteria

Summary

When creating a command:

  1. Detect location (project vs global)
  2. Show patterns to frame the conversation
  3. Gather information (name, purpose, arguments, steps, tools)
  4. Generate optimized command with agent-executable instructions
  5. Create file at appropriate location
  6. Confirm and iterate as needed

Focus on creating commands that agents can execute autonomously, with clear steps, explicit tool usage, and proper error handling.

Installationen

Installationen 6
Globales Ranking #601 von 601

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So verwenden Sie diesen Skill

1

Install command-creator by running npx skills add cachemoney/agent-toolkit --skill command-creator in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.

2

Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.

3

Der Skill verbessert das Verständnis Ihres Agenten für command-creator, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.

Was Sie erhalten

Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.

Kompatibilität

Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.

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