| name | slash-command-factory |
| description | Generate custom Claude Code slash commands through intelligent 5-7 question flow. Creates powerful commands for business research, content analysis, healthcare compliance, API integration, documentation automation, and workflow optimization. Outputs organized commands to generated-commands/ with validation and installation guidance. |
Slash Command Factory
A comprehensive system for generating production-ready Claude Code slash commands through a simple question-based workflow.
What This Skill Does
This skill helps you create custom slash commands for Claude Code by:
- Asking 5-7 straightforward questions about your command needs
- Generating complete command .md files with proper YAML frontmatter
- Providing 10 powerful preset commands for common use cases
- Validating command format and syntax
- Creating well-organized folder structures
- Offering installation guidance
Output: Complete slash commands ready to use in Claude Code
Official Command Structure Patterns
This skill generates commands following three official patterns from Anthropic documentation:
Pattern A: Simple (Context → Task)
Best for: Straightforward tasks with clear input/output
Example: Code review, file updates, simple analysis
Official Reference: code-review.md
Structure:
---
allowed-tools: Bash(git diff:*), Bash(git log:*)
description: Purpose description
---
## Context
- Current state: !`bash command`
- Additional data: !`another command`
## Your task
[Clear instructions with numbered steps]
[Success criteria]
When to use:
- Simple, focused tasks
- Quick analysis or reviews
- Straightforward workflows
- 1-3 bash commands for context
Pattern B: Multi-Phase (Discovery → Analysis → Task)
Best for: Complex discovery and documentation tasks
Example: Codebase analysis, comprehensive audits, system mapping
Official Reference: codebase-analysis.md
Structure:
---
allowed-tools: Bash(find:*), Bash(tree:*), Bash(ls:*), Bash(grep:*), Bash(wc:*), Bash(du:*)
description: Comprehensive purpose
---
# Command Title
## Phase 1: Project Discovery
### Directory Structure
!`find . -type d | sort`
### File Count Analysis
!`find . -type f | wc -l`
## Phase 2: Detailed Analysis
[More discovery commands]
[File references with @]
## Phase 3: Your Task
Based on all discovered information, create:
1. **Deliverable 1**
- Subsection
- Details
2. **Deliverable 2**
- Subsection
- Details
At the end, write output to [filename].md
When to use:
- Comprehensive analysis needed
- Multiple discovery phases
- Large amounts of context gathering
- 10+ bash commands for data collection
- Generate detailed documentation files
Pattern C: Agent-Style (Role → Process → Guidelines)
Best for: Specialized expert roles and coordination
Example: Domain experts, orchestrators, specialized advisors
Official Reference: openapi-expert.md
Structure:
---
name: command-name
description: |
Multi-line description for complex purpose
explaining specialized role
color: yellow
---
You are a [specialized role] focusing on [domain expertise].
**Core Responsibilities:**
1. **Responsibility Area 1**
- Specific tasks
- Expected outputs
2. **Responsibility Area 2**
- Specific tasks
- Expected outputs
**Working Process:**
1. [Step 1 in workflow]
2. [Step 2 in workflow]
3. [Step 3 in workflow]
**Important Considerations:**
- [Guideline 1]
- [Guideline 2]
- [Constraint or best practice]
When you encounter [scenario], [action to take].
When to use:
- Need specialized domain expertise
- Orchestrating complex workflows
- Coordinating multiple sub-processes
- Acting as expert advisor
- Require specific procedural guidelines
Comprehensive Naming Convention
Command File Naming Rules
All slash command files MUST follow kebab-case convention:
Format: [verb]-[noun].md, [noun]-[verb].md, or [domain]-[action].md
Rules:
- Case: Lowercase only with hyphens as separators
- Length: 2-4 words maximum
- Characters: Only
[a-z0-9-] allowed (letters, numbers, hyphens)
- Start/End: Must begin and end with letter or number (not hyphen)
- No: Spaces, underscores, camelCase, TitleCase, or special characters
Conversion Algorithm
User Input → Command Name
Input: "Analyze customer feedback and generate insights"
↓
1. Extract action: "analyze"
2. Extract target: "feedback"
3. Combine: "analyze-feedback"
4. Validate: Matches [a-z0-9-]+ pattern ✓
5. Output: analyze-feedback.md
More Examples:
- "Review pull requests" →
pr-review.md or review-pr.md
- "Generate API documentation" →
api-document.md or document-api.md
- "Update README files" →
update-readme.md or readme-update.md
- "Audit security compliance" →
security-audit.md or compliance-audit.md
- "Research market trends" →
research-market.md or market-research.md
- "Analyze code quality" →
code-analyze.md or analyze-code.md
Official Examples (From Anthropic Docs)
Correct:
- ✅
code-review.md (verb-noun)
- ✅
codebase-analysis.md (noun-noun compound)
- ✅
update-claude-md.md (verb-noun-qualifier)
- ✅
openapi-expert.md (domain-role)
Incorrect:
- ❌
code_review.md (snake_case - wrong)
- ❌
CodeReview.md (PascalCase - wrong)
- ❌
codeReview.md (camelCase - wrong)
- ❌
review.md (too vague - needs target)
- ❌
analyze-customer-feedback-data.md (too long - >4 words)
Bash Permission Patterns
Critical Rule: No Wildcards
❌ NEVER ALLOWED:
allowed-tools: Bash
This wildcard permission is prohibited per official Anthropic patterns.
✅ ALWAYS REQUIRED:
allowed-tools: Bash(git status:*), Bash(git diff:*), Bash(git log:*)
Must specify exact commands with wildcards only for subcommands.
Official Permission Patterns
Based on Anthropic's documented examples:
Git Operations (code-review, update-docs):
allowed-tools: Bash(git status:*), Bash(git diff:*), Bash(git log:*), Bash(git branch:*), Bash(git add:*), Bash(git commit:*)
File Discovery (codebase-analysis):
allowed-tools: Bash(find:*), Bash(tree:*), Bash(ls:*), Bash(du:*)
Content Analysis (comprehensive discovery):
allowed-tools: Bash(grep:*), Bash(wc:*), Bash(head:*), Bash(tail:*), Bash(cat:*)
Data Processing (custom analysis):
allowed-tools: Bash(awk:*), Bash(sed:*), Bash(sort:*), Bash(uniq:*)
Combined Patterns (multi-phase commands):
allowed-tools: Bash(find:*), Bash(tree:*), Bash(ls:*), Bash(grep:*), Bash(wc:*), Bash(du:*), Bash(head:*), Bash(tail:*), Bash(cat:*), Bash(touch:*)
Permission Selection Guide
| Command Type | Bash Permissions | Example Commands |
|---|
| Git Commands | git status, git diff, git log, git branch | code-review, commit-assist |
| Discovery | find, tree, ls, du | codebase-analyze, structure-map |
| Analysis | grep, wc, head, tail, cat | search-code, count-lines |
| Update | git diff, find, grep | update-docs, sync-config |
| Data Processing | awk, sed, sort, uniq | parse-data, format-output |
| Comprehensive | All of the above | full-audit, system-analyze |
Two Paths to Generate Commands
Path 1: Quick-Start Presets (30 seconds)
Choose from 10 powerful preset commands:
Business & Research:
- /research-business - Comprehensive market research and competitive analysis
- /research-content - Multi-platform content trend analysis and SEO strategy
Healthcare & Compliance:
3. /medical-translate - Translate medical terminology to 8th-10th grade (German/English)
4. /compliance-audit - HIPAA/GDPR/DSGVO compliance validation
Development & Integration:
5. /api-build - Generate complete API integration code with tests
6. /test-auto - Auto-generate comprehensive test suites
Documentation & Knowledge:
7. /docs-generate - Automated documentation creation
8. /knowledge-mine - Extract and structure insights from documents
Workflow & Productivity:
9. /workflow-analyze - Analyze and optimize business processes
10. /batch-agents - Launch and coordinate multiple agents for complex tasks
Path 2: Custom Command (5-7 Questions)
Create a completely custom command for your specific needs.
Question Flow (Custom Path)
Question 1: Command Purpose
"What should this slash command do?
Be specific about its purpose and when you'll use it.
Examples:
- 'Analyze customer feedback and generate actionable insights'
- 'Generate HIPAA-compliant API documentation'
- 'Research market trends and create content strategy'
- 'Extract key insights from research papers'
Your command's purpose: ___"
Question 2: Arguments (Auto-Determined)
The skill automatically determines if your command needs arguments based on the purpose.
If arguments are needed, they will use $ARGUMENTS format:
- User types:
/your-command argument1 argument2
- Command receives:
$ARGUMENTS = "argument1 argument2"
Examples:
/research-business "Tesla" "EV market" → $ARGUMENTS = "Tesla EV market"/medical-translate "Myokardinfarkt" "de" → $ARGUMENTS = "Myokardinfarkt de"
No user input needed - skill decides intelligently.
Question 3: Which Tools?
"Which Claude Code tools should this command use?
Available tools:
- Read - Read files
- Write - Create files
- Edit - Modify files
- Bash - Execute shell commands (MUST specify exact commands)
- Grep - Search code
- Glob - Find files by pattern
- Task - Launch agents
CRITICAL: For Bash, you MUST specify exact commands, not wildcards.
Bash Examples:
- ✅ Bash(git status:), Bash(git diff:), Bash(git log:*)
- ✅ Bash(find:), Bash(tree:), Bash(ls:*)
- ✅ Bash(grep:), Bash(wc:), Bash(head:*)
- ❌ Bash (wildcard not allowed per official patterns)
Tool Combination Examples:
- Git command: Read, Bash(git status:), Bash(git diff:)
- Code generator: Read, Write, Edit
- Discovery command: Bash(find:), Bash(tree:), Bash(grep:*)
- Analysis command: Read, Grep, Task (launch agents)
Your tools (comma-separated): ___"
Question 4: Agent Integration
"Does this command need to launch agents for specialized tasks?
Examples of when to use agents:
- Complex analysis (launch rr-architect, rr-security)
- Implementation tasks (launch rr-frontend, rr-backend)
- Quality checks (launch rr-qa, rr-test-runner)
Options:
- No agents - Command handles everything itself
- Launch agents - Delegate to specialized agents
Your choice (1 or 2): ___"
If "2", ask: "Which agents should it launch? ___"
Question 5: Output Type
"What type of output should this command produce?
- Analysis - Research report, insights, recommendations
- Files - Generated code, documentation, configs
- Action - Execute tasks, run workflows, deploy
- Report - Structured report with findings and next steps
Your choice (1, 2, 3, or 4): ___"
Question 6: Model Preference (Optional)
"Which Claude model should this command use?
- Default - Inherit from main conversation (recommended)
- Sonnet - Best for complex tasks
- Haiku - Fastest, cheapest (for simple commands)
- Opus - Maximum capability (for critical tasks)
Your choice (1, 2, 3, or 4) or press Enter for default: ___"
Question 7: Additional Features (Optional)
"Any special features?
Optional features:
- Bash execution - Run shell commands and include output (!
command)
- File references - Include file contents (@file.txt)
- Context gathering - Read project files for context
Features you need (comma-separated) or press Enter to skip: ___"
Generation Process
After collecting answers:
- Generate YAML Frontmatter:
---
description: [From command purpose]
argument-hint: [If $ARGUMENTS needed]
allowed-tools: [From tool selection]
model: [If specified]
---
- Generate Command Body:
[Purpose-specific instructions]
[If uses agents]:
1. **Launch [agent-name]** with [specific task]
2. Coordinate workflow
3. Validate results
[If uses bash]:
- Context: !`bash command`
[If uses file refs]:
- Review: @file.txt
Success Criteria: [Based on output type]
- Create Folder Structure:
generated-commands/[command-name]/
├── [command-name].md # Command file (ROOT)
├── README.md # Installation guide (ROOT)
├── TEST_EXAMPLES.md # Testing examples (ROOT)
└── [folders if needed] # standards/, examples/, scripts/
- Validate Format:
- ✅ YAML frontmatter valid
- ✅ $ARGUMENTS syntax correct (if used)
- ✅ allowed-tools format proper
- ✅ Folder organization clean
- Provide Installation Instructions:
Your command is ready!
Output location: generated-commands/[command-name]/
To install:
1. Copy the command file:
cp generated-commands/[command-name]/[command-name].md .claude/commands/
2. Restart Claude Code (if already running)
3. Test:
/[command-name] [arguments]
Preset Command Details
1. /research-business
Purpose: Comprehensive business and market research
Arguments: $ARGUMENTS (company or market to research)
YAML:
---
description: Comprehensive business and market research with competitor analysis
argument-hint: [company/market] [industry]
allowed-tools: Read, Bash, Grep
---
What it does:
- Market size and trends analysis
- Competitor SWOT analysis
- Opportunity identification
- Industry landscape overview
- Strategic recommendations
2. /research-content
Purpose: Multi-platform content trend analysis
Arguments: $ARGUMENTS (topic to research)
YAML:
---
description: Multi-platform content trend analysis for data-driven content strategy
argument-hint: [topic] [platforms]
allowed-tools: Read, Bash
---
What it does:
- Analyze trends across Google, Reddit, YouTube, Medium, LinkedIn, X
- User intent analysis (informational, commercial, transactional)
- Content gap identification
- SEO-optimized outline generation
- Platform-specific publishing strategies
3. /medical-translate
Purpose: Translate medical terminology to patient-friendly language
Arguments: $ARGUMENTS (medical term and language)
YAML:
---
description: Translate medical terminology to 8th-10th grade reading level (German/English)
argument-hint: [medical-term] [de|en]
allowed-tools: Read
---
What it does:
- Translate complex medical terms
- Simplify to 8th-10th grade reading level
- Validate with Flesch-Kincaid (EN) or Wiener Sachtextformel (DE)
- Preserve clinical accuracy
- Provide patient-friendly explanations
4. /compliance-audit
Purpose: Check code for regulatory compliance
Arguments: $ARGUMENTS (path and compliance standard)
YAML:
---
description: Audit code for HIPAA/GDPR/DSGVO compliance requirements
argument-hint: [code-path] [hipaa|gdpr|dsgvo|all]
allowed-tools: Read, Grep, Task
---
What it does:
- Scan for PHI/PII handling
- Check encryption requirements
- Verify audit logging
- Validate data subject rights
- Generate compliance report
5. /api-build
Purpose: Generate complete API integration code
Arguments: $ARGUMENTS (API name and endpoints)
YAML:
---
description: Generate complete API client with error handling and tests
argument-hint: [api-name] [endpoints]
allowed-tools: Read, Write, Edit, Bash, Task
---
What it does:
- Generate API client classes
- Add error handling and retries
- Create authentication logic
- Generate unit and integration tests
- Add usage documentation
6. /test-auto
Purpose: Auto-generate comprehensive test suites
Arguments: $ARGUMENTS (file path and test type)
YAML:
---
description: Auto-generate comprehensive test suite with coverage analysis
argument-hint: [file-path] [unit|integration|e2e]
allowed-tools: Read, Write, Bash
---
What it does:
- Analyze code to test
- Generate test cases (happy path, edge cases, errors)
- Add test fixtures and mocks
- Calculate coverage
- Provide testing documentation
7. /docs-generate
Purpose: Automated documentation generation
Arguments: $ARGUMENTS (code path and doc type)
YAML:
---
description: Auto-generate documentation from code (API docs, README, architecture)
argument-hint: [code-path] [api|readme|architecture|all]
allowed-tools: Read, Write, Grep
---
What it does:
- Extract code structure and functions
- Generate API documentation
- Create README with usage examples
- Build architecture diagrams (Mermaid)
- Add code examples
8. /knowledge-mine
Purpose: Extract structured insights from documents
Arguments: $ARGUMENTS (document path and output format)
YAML:
---
description: Extract and structure knowledge from documents into actionable insights
argument-hint: [doc-path] [faq|summary|kb|all]
allowed-tools: Read, Grep
---
What it does:
- Read and analyze documents
- Extract key insights
- Generate FAQs
- Create knowledge base articles
- Summarize findings
9. /workflow-analyze
Purpose: Analyze and optimize business workflows
Arguments: $ARGUMENTS (workflow description)
YAML:
---
description: Analyze workflows and provide optimization recommendations
argument-hint: [workflow-description]
allowed-tools: Read, Task
---
What it does:
- Map current workflow
- Identify bottlenecks
- Suggest automation opportunities
- Calculate efficiency gains
- Create implementation roadmap
10. /batch-agents
Purpose: Launch multiple coordinated agents
Arguments: $ARGUMENTS (agent names and task)
YAML:
---
description: Launch and coordinate multiple agents for complex tasks
argument-hint: [agent-names] [task-description]
allowed-tools: Task
---
What it does:
- Parse agent list
- Launch agents in parallel (if safe) or sequential
- Coordinate outputs
- Integrate results
- Provide comprehensive summary
Output Structure
Commands are generated in your project's root directory:
[your-project]/
└── generated-commands/
└── [command-name]/
├── [command-name].md # Command file (ROOT level)
├── README.md # Installation guide (ROOT level)
├── TEST_EXAMPLES.md # Testing guide (ROOT level - if applicable)
│
├── standards/ # Only if command has standards
├── examples/ # Only if command has examples
└── scripts/ # Only if command has helper scripts
Organization Rules:
- All .md files in ROOT directory
- Supporting folders separate (standards/, examples/, scripts/)
- No mixing of different types in same folder
- Clean, hierarchical structure
Installation
After generation:
-
Review output:
ls generated-commands/[command-name]/
-
Copy to Claude Code (when ready):
cp generated-commands/[command-name]/[command-name].md .claude/commands/
cp generated-commands/[command-name]/[command-name].md ~/.claude/commands/
-
Restart Claude Code (if running)
-
Test command:
/[command-name] [arguments]
Usage Examples
Generate a Preset Command
@slash-command-factory
Use the /research-business preset
Output: Complete business research command ready to install
Generate a Custom Command
@slash-command-factory
Create a custom command for analyzing customer feedback and generating product insights
Skill asks 5-7 questions → Generates complete command → Validates format → Provides installation steps
Command Format (What Gets Generated)
Example generated command (my-command.md):
---
description: Brief description of what the command does
argument-hint: [arg1] [arg2]
allowed-tools: Read, Write, Bash
model: claude-3-5-sonnet-20241022
---
# Command Instructions
Do [task] with "$ARGUMENTS":
1. **Step 1**: First action
2. **Step 2**: Second action
3. **Step 3**: Generate output
**Success Criteria**:
- Criterion 1
- Criterion 2
- Criterion 3
Validation
Every generated command is automatically validated for:
- ✅ Valid YAML frontmatter (proper syntax, required fields)
- ✅ Correct argument format ($ARGUMENTS, not $1 $2 $3)
- ✅ allowed-tools syntax (comma-separated string)
- ✅ Clean folder organization (if folders used)
- ✅ No placeholder text
If validation fails, you'll get specific fix instructions.
Best Practices
For Command Design:
- Keep commands focused (one clear purpose)
- Use descriptive names (kebab-case for files)
- Document expected arguments clearly
- Include success criteria
- Add examples in TEST_EXAMPLES.md
For Tool Selection:
- Read: For analyzing files
- Write/Edit: For generating/modifying files
- Bash: For system commands, web research
- Task: For launching agents
- Grep/Glob: For searching code
For Agent Integration:
- Use Task tool to launch agents
- Specify which agents clearly
- Coordinate outputs
- Document agent roles
Important Notes
Arguments:
- ✅ Always use
$ARGUMENTS (all arguments as one string)
- ❌ Never use
$1, $2, $3 (positional - not used by this factory)
Folder Organization:
- ✅ All .md files in command root directory
- ✅ Supporting folders separate (standards/, examples/, scripts/)
- ✅ No mixing of different types
Output Location:
- Commands generate to:
./generated-commands/[command-name]/
- User copies to:
.claude/commands/[command-name].md (when ready)
Example Invocations
Use a Preset
@slash-command-factory
Generate the /research-content preset command
→ Creates content research command with all features
Create Custom Healthcare Command
@slash-command-factory
Create a command that generates German PTV 10 therapy applications
Skill asks:
- Purpose? (Generate PTV 10 applications)
- Tools? (Read, Write, Task)
- Agents? (Yes - health-sdk-builder related agents)
- Output? (Files - therapy application documents)
- Model? (Sonnet - for quality)
Result: /generate-ptv10 command ready to use
Create Business Intelligence Command
@slash-command-factory
Build a command for competitive SWOT analysis
Skill asks 5-7 questions → Generates /swot-analysis command → Validates → Ready to install
Integration with Factory Agents
Works with:
- factory-guide (can delegate to this skill via prompts-guide pattern)
- Existing slash commands (/build, /validate-output, etc.)
Complements:
- skills-guide (builds Skills)
- prompts-guide (builds Prompts)
- agents-guide (builds Agents)
- slash-command-factory (builds Commands) ← This skill
Complete ecosystem for building all Claude Code augmentations!
Output Validation
Generated commands are validated for:
YAML Frontmatter:
- Has
description field
- Proper YAML syntax
- Valid frontmatter fields only
Arguments:
- Uses $ARGUMENTS if needed
- Has argument-hint if $ARGUMENTS used
- No $1, $2, $3 positional args
Tools:
- Valid tool names
- Proper comma-separated format
- Appropriate for command purpose
Organization:
- .md files in root
- Folders properly separated
- No scattered files
Success Criteria
Generated commands should:
- ✅ Have valid YAML frontmatter
- ✅ Use $ARGUMENTS (never positional)
- ✅ Work when copied to .claude/commands/
- ✅ Execute correctly with arguments
- ✅ Produce expected output
- ✅ Follow organizational standards
Version: 1.0.0
Last Updated: October 28, 2025
Compatible: Claude Code (all versions with slash command support)
Build powerful custom slash commands in minutes! ⚡
