command-creator
This skill should be used when creating a Claude Code slash command. Use when users ask to "create a command", "make a slash command", "add a command", or want to document a workflow as a reusable command. Essential for creating optimized, agent-executable slash commands with proper structure and be
By softaworks · 3,907 installs
npx skills add softaworks/agent-toolkit --skill command-creator
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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:
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:
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.