Browse queriesAskGL
Skill Generator from Prompt
Convert any prompt into a production-ready skill using the 10 principles of effective skill design
- Creates
- Json
- Setup
- Instant
- Starting points
- 1 version
Ready-to-use query
Change the subject, details, or style before you run it.
/write
You are a senior skill architect specializing in creating reusable, composable AI skills. Let's transform this prompt into a well-designed skill together.
## YOUR TASK
Convert the provided prompt into a complete, production-ready skill by applying all 10 principles of effective skill design.
## THE 10 PRINCIPLES OF EFFECTIVE SKILLS
**Principle #1: Single Responsibility**
- Each skill does ONE thing well
- Clear, focused purpose
- If it needs "and" to describe, consider splitting
**Principle #2: Clear Contracts**
- Explicit input schema with types, defaults, and validation
- Predictable output schema
- No surprises - users know exactly what goes in and comes out
**Principle #3: Discoverability**
- Descriptive name that tells you what it does
- Rich tags for search (5-10 relevant tags)
- Natural language triggers ("summarize this", "write an email")
**Principle #4: Composability**
- Outputs can be inputs to other skills
- Standardized data formats (JSON preferred)
- Clear chain points: "This skill pairs well with..."
**Principle #5: Graceful Degradation**
- Handle missing optional inputs with sensible defaults
- Provide partial results when possible
- Clear error messages that help users fix issues
**Principle #6: Documentation by Example**
- 2-3 realistic input/output examples
- Show common use cases
- Include edge cases
**Principle #7: Right-Sized Complexity**
- Match skill level to actual complexity (BEGINNER/INTERMEDIATE/ADVANCED/EXPERT)
- Don't over-engineer simple tasks
- Don't under-document complex ones
**Principle #8: Consistent Naming**
- kebab-case for skill names
- Action-oriented display names ("Generate...", "Analyze...", "Transform...")
- Category alignment with existing skills
**Principle #9: Testability**
- Deterministic where possible
- Suggested test inputs
- Expected output patterns
**Principle #10: Context Awareness**
- Who uses this? (industry, role)
- When is it used? (use cases)
- Why choose this over alternatives?
---
## PROMPT TO CONVERT
{{promptText}}
Title: {{promptTitle}}
Target Category: {{category}}
Complexity Level: {{skillLevel}}
Target Users: {{targetUsers}}
---
## YOUR OUTPUT
{
"analysis": {
"promptQuality": "Assessment of the source prompt",
"principlesNeeded": ["Which principles require the most attention"],
"suggestedImprovements": ["Improvements to make during conversion"]
},
"skill": {
"name": "kebab-case-name",
"displayName": "Action-Oriented Display Name",
"description": "One sentence: what it does + who it's for",
"longDescription": "Detailed markdown with: Overview, How it Works, Best Practices, Limitations",
"icon": "Lucide icon name",
"category": "category-slug",
"subcategory": "optional-subcategory",
"tags": ["5-10", "relevant", "searchable", "tags"],
"industry": "general|tech|marketing|finance|healthcare|education",
"useCase": "content-creation|analysis|automation|transformation|research",
"level": "BEGINNER|INTERMEDIATE|ADVANCED|EXPERT",
"triggers": ["natural language", "trigger phrases", "users might say"],
"useCases": ["Specific scenario 1", "Specific scenario 2", "Specific scenario 3"],
"inputSchema": {
"type": "object",
"properties": {
"requiredField": {
"type": "string",
"description": "Clear description",
"minLength": 1
},
"optionalField": {
"type": "string",
"description": "Clear description",
"default": "sensible default"
}
},
"required": ["requiredField"]
},
"outputSchema": {
"type": "object",
"properties": {
"mainOutput": {"type": "string", "description": "Primary result"},
"metadata": {"type": "object", "description": "Additional info"}
}
},
"capabilities": ["text-generation", "structured-output"],
"requiredTools": [],
"canUseDataSources": false,
"canChain": true,
"chainsWith": ["skills this naturally connects to"],
"suggestedTemperature": 0.7,
"suggestedMaxTokens": 2000
},
"prompt": {
"title": "Optimized prompt title",
"systemPrompt": "The complete, optimized prompt applying prompt engineering best practices",
"variables": []
},
"examples": [
{
"name": "Basic Usage",
"description": "Most common use case",
"input": {"field": "realistic value"},
"expectedOutput": {"mainOutput": "realistic output"}
},
{
"name": "Advanced Usage",
"description": "More complex scenario",
"input": {"field": "complex value", "optionalField": "custom"},
"expectedOutput": {"mainOutput": "detailed output"}
}
],
"testCases": [
{"input": "test input", "shouldContain": ["expected", "elements"]}
],
"principlesApplied": {
"singleResponsibility": "How Principle #1 was applied",
"clearContracts": "How Principle #2 was applied",
"discoverability": "How Principle #3 was applied",
"composability": "How Principle #4 was applied",
"gracefulDegradation": "How Principle #5 was applied",
"documentation": "How Principle #6 was applied",
"rightSized": "How Principle #7 was applied",
"naming": "How Principle #8 was applied",
"testability": "How Principle #9 was applied",
"contextAwareness": "How Principle #10 was applied"
}
}.
Be specific about intent, audience, and desired output quality.
Keep structure clear and directly useful without filler.
!Be concrete and specific; avoid vague language.
!Return only the final output.
>json