
Nav Skill Creator
- 2 installs
- 32 repo stars
- Updated January 23, 2026
- dkyazzentwatwa/supernavigator
Analyzes codebase patterns and generates a custom project skill with triggers, functions, and templates for repetitive workflows.
About
Analyzes codebase patterns and generates project-specific skills to automate repetitive workflows. A developer uses it when a project needs pattern enforcement or automation.
- Analyzes codebase patterns to identify repetitive workflows
- Generates a custom skill with triggers, functions, and templates
Nav Skill Creator by the numbers
- 2 all-time installs (skills.sh)
- Ranked #607 of 781 Skill Development skills by installs in the Skillselion catalog
- Data as of Jul 29, 2026 (Skillselion catalog sync)
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| Installs | 2 |
|---|---|
| repo stars | ★ 32 |
| Last updated | January 23, 2026 |
| Repository | dkyazzentwatwa/supernavigator ↗ |
What it does
Analyzes codebase patterns and generates a custom project skill with triggers, functions, and templates for repetitive workflows.
Files
Navigator Skill Creator
Create project-specific skills by analyzing codebase patterns and automating repetitive workflows.
When to Invoke
Auto-invoke when user mentions:
- "Create a skill for [pattern]"
- "Automate this workflow"
- "We keep doing X manually"
- "Enforce this pattern"
- "Generate boilerplate for [feature type]"
- "We need consistency for [task type]"
What This Does
1. Analyzes codebase to understand project patterns 2. Identifies best practices from existing code 3. Generates skill with:
- Auto-invocation triggers
- Predefined functions
- Templates
- Examples
4. Tests the generated skill 5. Documents the new skill
Execution Steps
Step 1: Understand Skill Request
Ask clarifying questions:
- What pattern/workflow to automate?
- What triggers should invoke this skill?
- What output format is expected?
- Are there existing examples in the codebase?
Example dialogue:
User: "Create a skill for adding React components"
Assistant: "I'll analyze your codebase to understand React component patterns.
- What directory are components in?
- Do you use TypeScript or JavaScript?
- Do you want tests generated automatically?
- Are there style files (CSS/SCSS) per component?"Step 2: Analyze Codebase Patterns
Use Task agent to explore (saves 60-80% tokens):
Use Task agent with subagent_type=Explore:
"Find existing [pattern type] in codebase:
- Locate all [files matching pattern]
- Identify common structure
- Extract best practices
- Find configuration files
- Return summary of findings"What to look for:
- File naming conventions (kebab-case, PascalCase, etc.)
- Directory structure patterns
- Import/export patterns
- Testing patterns
- Configuration patterns
- Documentation patterns
Example for React components:
Task agent finds:
- Components in src/components/
- PascalCase naming (UserProfile.tsx)
- Co-located tests (UserProfile.test.tsx)
- Props interfaces defined above component
- Export default at bottomStep 3: Design Skill Structure
Determine skill metadata:
name: [project]-[pattern-type]
description: [When to auto-invoke + what it does]
allowed-tools: [Read, Write, Edit, Grep, Glob, Bash, Task]
version: 1.0.0Plan directory structure:
skills/[skill-name]/
├── SKILL.md # Main instructions
├── functions/ # Python helper scripts
│ └── [generator].py
├── examples/ # Reference implementations
│ └── [example].[ext]
└── templates/ # Output format templates
└── [template].[ext]Design predefined functions:
- What repetitive logic can be automated?
- What validation should be enforced?
- What formatting ensures consistency?
Example functions for frontend-component skill:
component_generator.py- Generate component boilerplatetest_generator.py- Generate test filestyle_generator.py- Generate style filename_validator.py- Validate component naming
Step 4: Generate Skill Files
4.1 Create SKILL.md
---
name: [skill-name]
description: [Auto-invocation triggers + purpose]
allowed-tools: [List of tools]
version: 1.0.0
---
# [Skill Title]
[Brief description of what this skill does]
## When to Invoke
Auto-invoke when user says:
- "[trigger phrase 1]"
- "[trigger phrase 2]"
- "[trigger phrase 3]"
## What This Does
1. [Step 1 overview]
2. [Step 2 overview]
3. [Step 3 overview]
## Execution Steps
### Step 1: [Step Name]
[Detailed instructions for this step]
**Use predefined function**: `functions/[function-name].py`4.2 Create Predefined Functions
# functions/[generator].py
def generate_[output](name, config):
"""
Generate [output type] based on project patterns.
Args:
name: [Description]
config: [Description]
Returns:
[output]: [Description]
"""
# Implementation based on codebase analysis
pass4.3 Create Examples
examples/
└── [reference-implementation].[ext]
- Real example from codebase (best practice)
- Shows expected structure
- Demonstrates conventions4.4 Create Templates
templates/
└── [output-template].[ext]
- Skeleton structure with placeholders
- ${VAR_NAME} for substitution
- Comments explaining sectionsStep 5: Test Generated Skill
5.1 Verify skill loads:
# In project root
grep -r "name: [skill-name]" skills/5.2 Test auto-invocation:
In Claude Code conversation:
"[Use one of the auto-invoke trigger phrases]"
Expected: Skill should be detected and loaded5.3 Test execution:
- Run through skill steps
- Verify functions work correctly
- Check output matches template
- Validate generated code follows patterns
5.4 Iterate if needed:
- Fix function bugs
- Improve templates
- Add missing examples
- Clarify instructions
Step 6: Document New Skill
Update project documentation:
1. CLAUDE.md - Add to skills section:
#### [Skill Name]
**Auto-invoke**: "[trigger phrase]"
**Purpose**: [What it does]
**Generates**: [Output type]2. README.md - Add to skills list:
- **[skill-name]**: [Brief description]3. .agent/system/plugin-patterns.md - Add to skill registry:
### [Skill Name]
**Created**: [Date]
**Pattern**: [What pattern it enforces]
**Functions**: [List of predefined functions]Register in plugin.json (if applicable):
{
"skills": [
{
"name": "[skill-name]",
"path": "skills/[skill-name]/SKILL.md"
}
]
}---
Example Workflows
Example 1: Create Skill for Adding API Endpoints
User: "Create a skill for adding REST API endpoints"
Execution:
1. Clarify:
- Which framework? (Express, Fastify, etc.)
- Where are routes defined?
- Authentication required?
- Testing strategy?
2. Analyze (via Task agent):
Find existing API endpoints:
- Routes in api/routes/
- Controllers in api/controllers/
- Middleware in api/middleware/
- Tests in tests/api/3. Design:
name: backend-api-endpoint
description: Add new REST API endpoint following project conventions. Use when user says "add endpoint", "create API", or "new route".
allowed-tools: Read, Write, Edit, Grep, Glob, Bash4. Generate:
skills/backend-api-endpoint/
├── SKILL.md
├── functions/
│ ├── endpoint_generator.py
│ └── route_validator.py
├── examples/
│ └── user-endpoint.ts
└── templates/
├── route-template.ts
└── test-template.spec.ts5. Test:
User: "Add a POST /posts endpoint"
Skill: Auto-invoked, generates route + controller + test
Verify: Files follow project conventions6. Document: Update CLAUDE.md, README.md, plugin-patterns.md
Example 2: Create Skill for React Components
User: "Automate creating new React components"
Execution:
1. Clarify:
- TypeScript or JavaScript?
- Functional or class components?
- Style approach? (CSS modules, styled-components, etc.)
- Test library? (Jest, React Testing Library, etc.)
2. Analyze (via Task agent):
Find React components:
- Components in src/components/
- PascalCase naming
- TypeScript (.tsx)
- CSS modules (.module.css)
- Tests with RTL3. Design:
name: frontend-component
description: Create new React component with TypeScript, styles, and tests. Use when user says "create component", "add component", or "new React component".
allowed-tools: Read, Write, Edit, Grep, Glob, Bash4. Generate:
skills/frontend-component/
├── SKILL.md
├── functions/
│ ├── component_generator.py
│ ├── test_generator.py
│ └── style_generator.py
├── examples/
│ ├── Button.tsx
│ └── Button.test.tsx
└── templates/
├── component-template.tsx
├── test-template.test.tsx
└── style-template.module.css5. Test:
User: "Create a UserProfile component"
Skill: Auto-invoked, generates component + test + styles
Verify: Props interface, exports, naming correct6. Document: Update project docs
---
Output Format
After generating skill, show summary:
✅ Skill Created: [skill-name]
Structure:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📁 skills/[skill-name]/
├── SKILL.md
├── functions/
│ └── [N functions created]
├── examples/
│ └── [N examples added]
└── templates/
└── [N templates created]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Auto-Invocation Triggers:
- "[trigger 1]"
- "[trigger 2]"
- "[trigger 3]"
Next Steps:
1. Test the skill: "[example trigger phrase]"
2. Iterate if needed
3. Documentation updated
Try it now: "[example usage]"---
Best Practices
Pattern Analysis
- Use Task agent for codebase exploration (saves 60-80% tokens)
- Look at 3-5 examples minimum (find patterns vs outliers)
- Identify conventions explicitly followed
- Note edge cases in comments
Skill Design
- Keep skills focused (one pattern per skill)
- Clear auto-invocation triggers (3-5 phrases)
- Minimal tools needed (add only what's required)
- Progressive disclosure (details in functions, not main instructions)
Function Creation
- One function = one responsibility
- Type hints and docstrings required
- Handle errors gracefully
- Return structured data (not print statements)
Template Design
- Use clear placeholders (${VAR_NAME})
- Include comments explaining sections
- Follow project style guide
- Provide sensible defaults
Testing
- Test with real project context
- Verify auto-invocation works
- Check output against best practices
- Iterate based on actual usage
---
Common Patterns to Automate
Backend Patterns
- REST API endpoints
- GraphQL resolvers
- Database migrations
- Background jobs
- Middleware functions
- Authentication guards
Frontend Patterns
- React/Vue/Svelte components
- Redux/Vuex store modules
- API client functions
- Form validation schemas
- Route definitions
- Style component creation
Infrastructure Patterns
- Docker service configs
- CI/CD pipeline steps
- Deployment scripts
- Environment configs
- Monitoring setup
Documentation Patterns
- API documentation
- Component documentation
- Architecture decision records (ADRs)
- Runbook entries
- Changelog entries
---
Troubleshooting
Skill Not Auto-Invoking
Problem: Skill created but doesn't trigger automatically
Solutions: 1. Check description has clear trigger phrases 2. Verify plugin.json includes skill registration 3. Reload Claude Code to refresh skill index 4. Test with exact trigger phrase from description
Functions Not Executing
Problem: Predefined functions throw errors
Solutions: 1. Check Python syntax is valid 2. Verify function imports are correct 3. Test function independently first 4. Check error messages in execution logs
Templates Not Matching Output
Problem: Generated code doesn't match project conventions
Solutions: 1. Re-analyze codebase for missed patterns 2. Update templates with correct structure 3. Add more examples showing variations 4. Validate against linter/formatter
Skill Too Broad
Problem: Skill tries to do too much
Solutions: 1. Split into multiple focused skills 2. Remove optional features to separate skills 3. Keep core pattern simple 4. Add extensions as separate skills
---
Success Criteria
This skill succeeds when:
- [ ] New skill auto-invokes correctly
- [ ] Generated output follows project conventions
- [ ] Functions execute without errors
- [ ] Templates produce valid code
- [ ] Examples are clear and relevant
- [ ] Documentation is updated
- [ ] Skill saves time vs manual work
---
The skill-creator is Navigator's self-improving engine - it learns your patterns and automates them 🔄
Example Feature Generator
This is an example of a generated skill created by nav-skill-creator.
When to Invoke
Auto-invoke when user says:
- "Create a new feature"
- "Add feature scaffolding"
- "Generate feature boilerplate"
What This Does
1. Asks for feature name and type 2. Analyzes existing features for patterns 3. Generates feature files following project conventions 4. Creates tests and documentation
Execution Steps
Step 1: Gather Feature Requirements
Ask user:
- Feature name (kebab-case)
- Feature type (API, UI, background job, etc.)
- Dependencies needed
- Testing requirements
Step 2: Analyze Existing Patterns
Use Task agent to explore codebase:
"Find existing features similar to [feature-type]:
- Locate feature files
- Identify structure patterns
- Extract naming conventions
- Find test patterns"Step 3: Generate Feature Files
Use predefined function: functions/feature_generator.py
# Generates feature structure based on analysis
generate_feature(name, feature_type, config)Creates:
- Feature implementation file
- Test file
- Configuration file (if needed)
- Documentation stub
Step 4: Validate Generated Files
Check:
- [ ] Files follow naming conventions
- [ ] Imports are correct
- [ ] Tests are generated
- [ ] Documentation is created
Step 5: Show Summary
Display created files and next steps for user.
---
Output Format
✅ Feature Created: [feature-name]
Files generated:
- features/[feature-name]/index.ts
- features/[feature-name]/[feature-name].test.ts
- features/[feature-name]/README.md
Next steps:
1. Implement feature logic in index.ts
2. Add test cases in [feature-name].test.ts
3. Document usage in README.md---
This is an example - actual generated skills will vary based on project patterns
#!/usr/bin/env python3
"""
Skill Generator - Example predefined function for nav-skill-creator
This is a reference implementation showing how predefined functions work.
Actual implementations will vary based on the skill being created.
"""
from typing import Dict, List, Optional
def generate_skill_structure(
skill_name: str,
description: str,
triggers: List[str],
tools: List[str] = None
) -> Dict[str, str]:
"""
Generate basic skill structure with YAML frontmatter and markdown body.
Args:
skill_name: Name of the skill (kebab-case)
description: When to auto-invoke and what the skill does
triggers: List of phrases that should auto-invoke the skill
tools: List of allowed tools (default: Read, Write, Edit, Grep, Glob, Bash)
Returns:
Dictionary with 'frontmatter' and 'body' keys containing the generated content
Example:
>>> generate_skill_structure(
... "example-skill",
... "Example skill for demo",
... ["create example", "add example"]
... )
{'frontmatter': '---\\nname: example-skill\\n...', 'body': '# Example Skill\\n...'}
"""
if tools is None:
tools = ["Read", "Write", "Edit", "Grep", "Glob", "Bash"]
# Generate YAML frontmatter
frontmatter = f"""---
name: {skill_name}
description: {description}
allowed-tools: {', '.join(tools)}
version: 1.0.0
---"""
# Generate markdown body
trigger_list = '\n'.join([f'- "{trigger}"' for trigger in triggers])
body = f"""
# {skill_name.replace('-', ' ').title()}
[Brief description of what this skill does]
## When to Invoke
Auto-invoke when user says:
{trigger_list}
## What This Does
1. [Step 1 overview]
2. [Step 2 overview]
3. [Step 3 overview]
## Execution Steps
### Step 1: [Step Name]
[Detailed instructions for this step]
### Step 2: [Step Name]
[Detailed instructions for this step]
### Step 3: [Step Name]
[Detailed instructions for this step]
---
## Output Format
```
✅ [Task Complete]
[Summary of what was generated or accomplished]
```
---
## Best Practices
- [Best practice 1]
- [Best practice 2]
- [Best practice 3]
---
**[Closing statement about the skill]**
"""
return {
'frontmatter': frontmatter,
'body': body.strip(),
'full': f"{frontmatter}\n\n{body.strip()}"
}
def validate_skill_name(name: str) -> tuple[bool, Optional[str]]:
"""
Validate skill name follows conventions.
Args:
name: Skill name to validate
Returns:
Tuple of (is_valid, error_message)
Example:
>>> validate_skill_name("my-skill")
(True, None)
>>> validate_skill_name("MySkill")
(False, "Skill name must be kebab-case")
"""
import re
if not name:
return False, "Skill name cannot be empty"
if not re.match(r'^[a-z][a-z0-9]*(-[a-z0-9]+)*$', name):
return False, "Skill name must be kebab-case (lowercase, hyphens only)"
if len(name) > 50:
return False, "Skill name too long (max 50 characters)"
return True, None
def format_tool_list(tools: List[str]) -> str:
"""
Format list of tools for YAML frontmatter.
Args:
tools: List of tool names
Returns:
Comma-separated string of tools
Example:
>>> format_tool_list(["Read", "Write", "Edit"])
'Read, Write, Edit'
"""
return ', '.join(tools)
if __name__ == "__main__":
# Example usage
result = generate_skill_structure(
skill_name="example-generator",
description="Generate examples following project patterns",
triggers=["create example", "add example", "new example"]
)
print("Generated Skill:")
print("=" * 50)
print(result['full'])
print("=" * 50)
# Validate some names
test_names = ["my-skill", "MySkill", "my_skill", "skill-123"]
print("\nValidation Tests:")
for name in test_names:
valid, error = validate_skill_name(name)
status = "✅" if valid else "❌"
print(f"{status} {name}: {error or 'Valid'}")
${SKILL_TITLE}
${BRIEF_DESCRIPTION}
When to Invoke
Auto-invoke when user says:
- "${TRIGGER_1}"
- "${TRIGGER_2}"
- "${TRIGGER_3}"
What This Does
1. ${STEP_1_OVERVIEW} 2. ${STEP_2_OVERVIEW} 3. ${STEP_3_OVERVIEW}
Execution Steps
Step 1: ${STEP_1_NAME}
${STEP_1_INSTRUCTIONS}
Use predefined function (if applicable): functions/${FUNCTION_1_NAME}.py
Step 2: ${STEP_2_NAME}
${STEP_2_INSTRUCTIONS}
Use predefined function (if applicable): functions/${FUNCTION_2_NAME}.py
Step 3: ${STEP_3_NAME}
${STEP_3_INSTRUCTIONS}
---
Example Workflows
Example 1: ${EXAMPLE_1_TITLE}
User: "${EXAMPLE_1_USER_INPUT}"
Execution:
1. ${EXAMPLE_1_STEP_1} 2. ${EXAMPLE_1_STEP_2} 3. ${EXAMPLE_1_STEP_3}
Output:
${EXAMPLE_1_OUTPUT}---
Output Format
After completing task, show summary:
✅ ${SUCCESS_MESSAGE}
${OUTPUT_SUMMARY}
Next Steps:
1. ${NEXT_STEP_1}
2. ${NEXT_STEP_2}
3. ${NEXT_STEP_3}---
Best Practices
${BEST_PRACTICE_CATEGORY_1}
- ${BEST_PRACTICE_1}
- ${BEST_PRACTICE_2}
- ${BEST_PRACTICE_3}
${BEST_PRACTICE_CATEGORY_2}
- ${BEST_PRACTICE_4}
- ${BEST_PRACTICE_5}
- ${BEST_PRACTICE_6}
---
Troubleshooting
${PROBLEM_1}
Problem: ${PROBLEM_1_DESCRIPTION}
Solutions: 1. ${SOLUTION_1_1} 2. ${SOLUTION_1_2} 3. ${SOLUTION_1_3}
${PROBLEM_2}
Problem: ${PROBLEM_2_DESCRIPTION}
Solutions: 1. ${SOLUTION_2_1} 2. ${SOLUTION_2_2}
---
Success Criteria
This skill succeeds when:
- [ ] ${SUCCESS_CRITERION_1}
- [ ] ${SUCCESS_CRITERION_2}
- [ ] ${SUCCESS_CRITERION_3}
- [ ] ${SUCCESS_CRITERION_4}
---
${CLOSING_STATEMENT}