command-creator▌
davila7/claude-code-templates · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
This skill guides the creation of Claude Code slash commands - reusable workflows that can be invoked with /command-name in Claude Code conversations.
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:
- Check git repository status:
git rev-parse --is-inside-work-tree 2>/dev/null - Default location:
- If in git repo → Project-level:
.claude/commands/ - If not in git repo → Global:
~/.claude/commands/
- If in git repo → Project-level:
- 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/
- If user explicitly mentions "global" or "user-level" → Use
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
- ✅ CORRECT:
- File names match command names:
my-command.md→ invoked as/my-command - Description should be concise, action-oriented (appears in
/helpoutput)
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
-
Determine full file path:
- Project:
.claude/commands/[command-name].md - Global:
~/.claude/commands/[command-name].md
- Project:
-
Ensure directory exists:
mkdir -p [directory-path] -
Write the command file using the Write tool
-
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:
- Suggest testing:
You can test this command by running: /command-name [arguments] - Be ready to iterate based on feedback
- 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,gtcommands - 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:
- Detect location (project vs global)
- Show patterns to frame the conversation
- Gather information (name, purpose, arguments, steps, tools)
- Generate optimized command with agent-executable instructions
- Create file at appropriate location
- Confirm and iterate as needed
Focus on creating commands that agents can execute autonomously, with clear steps, explicit tool usage, and proper error handling.
How to use command-creator on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add command-creator
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches command-creator from GitHub repository davila7/claude-code-templates and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate command-creator. Access the skill through slash commands (e.g., /command-creator) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★44 reviews- ★★★★★Maya Ramirez· Dec 24, 2024
command-creator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Amelia Farah· Dec 16, 2024
Useful defaults in command-creator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Maya Menon· Dec 12, 2024
command-creator has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Kaira Ramirez· Nov 15, 2024
We added command-creator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Soo Verma· Nov 15, 2024
Registry listing for command-creator matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Carlos Taylor· Nov 7, 2024
I recommend command-creator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Maya Verma· Nov 3, 2024
command-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Carlos Sethi· Oct 26, 2024
command-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Jin Bhatia· Oct 22, 2024
I recommend command-creator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Jin Mehta· Oct 6, 2024
Solid pick for teams standardizing on skills: command-creator is focused, and the summary matches what you get after install.
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