prompt-engineering
Master prompt engineering for AI models: LLMs, image generators, video models. Techniques: chain-of-thought, few-shot, system prompts, negative prompts. Models: Claude, GPT-4, Gemini, FLUX, Veo, Stable Diffusion prompting. Use for: better AI outputs, consistent results, complex tasks, optimization. Triggers: prompt engineering, how to prompt, better prompts, prompt tips, prompting guide, llm prompting, image prompt, ai prompting, prompt optimization, prompt template, prompt structure, effective prompts, prompt techniques
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/101-skills/superpowers --skill prompt-engineering- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads prompt-engineering automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Install the belt CLI skill:
npx skills add belt-sh/cli
Prompt Engineering Guide
Master prompt engineering for AI models via inference.sh CLI.
Quick Start
Requires inference.sh CLI (
belt). Install instructions
belt login
# Well-structured LLM prompt
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "You are a senior software engineer. Review this code for security vulnerabilities:\n\n```python\nuser_input = request.args.get(\"query\")\nresult = db.execute(f\"SELECT * FROM users WHERE name = {user_input}\")\n```\n\nProvide specific issues and fixes."
}'
LLM Prompting
Basic Structure
[Role/Context] + [Task] + [Constraints] + [Output Format]
Role Prompting
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "You are an expert data scientist with 15 years of experience in machine learning. Explain gradient descent to a beginner, using simple analogies."
}'
Task Clarity
# Bad: vague
"Help me with my code"
# Good: specific
"Debug this Python function that should return the sum of even numbers from a list, but returns 0 for all inputs:
def sum_evens(numbers):
total = 0
for n in numbers:
if n % 2 == 0:
total += n
return total
Identify the bug and provide the corrected code."
Chain-of-Thought
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "Solve this step by step:\n\nA store sells apples for $2 each and oranges for $3 each. If someone buys 5 fruits and spends $12, how many of each fruit did they buy?\n\nThink through this step by step before giving the final answer."
}'
Few-Shot Examples
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "Convert these sentences to formal business English:\n\nExample 1:\nInput: gonna send u the report tmrw\nOutput: I will send you the report tomorrow.\n\nExample 2:\nInput: cant make the meeting, something came up\nOutput: I apologize, but I will be unable to attend the meeting due to an unforeseen circumstance.\n\nNow convert:\nInput: hey can we push the deadline back a bit?"
}'
Output Format Specification
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "Analyze the sentiment of these customer reviews. Return a JSON array with objects containing \"text\", \"sentiment\" (positive/negative/neutral), and \"confidence\" (0-1).\n\nReviews:\n1. \"Great product, fast shipping!\"\n2. \"Meh, its okay I guess\"\n3. \"Worst purchase ever, total waste of money\"\n\nReturn only valid JSON, no explanation."
}'
Constraint Setting
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "Summarize this article in exactly 3 bullet points. Each bullet must be under 20 words. Focus only on actionable insights, not background information.\n\n[article text]"
}'
Image Generation Prompting
Basic Structure
[Subject] + [Style] + [Composition] + [Lighting] + [Technical]
Subject Description
# Bad: vague
"a cat"
# Good: specific
belt app run falai/flux-dev --input '{
"prompt": "A fluffy orange tabby cat with green eyes, sitting on a vintage leather armchair"
}'
Style Keywords
belt app run falai/flux-dev --input '{
"prompt": "Portrait photograph of a woman, shot on Kodak Portra 400 film, soft natural lighting, shallow depth of field, nostalgic mood, analog photography aesthetic"
}'
Composition Control
belt app run falai/flux-dev --input '{
"prompt": "Wide establishing shot of a cyberpunk city skyline at night, rule of thirds composition, neon signs in foreground, towering skyscrapers in background, rain-slicked streets"
}'
Quality Keywords
photorealistic, 8K, ultra detailed, sharp focus, professional,
masterpiece, high quality, best quality, intricate details
Negative Prompts
belt app run falai/flux-dev --input '{
"prompt": "Professional headshot portrait, clean background",
"negative_prompt": "blurry, distorted, extra limbs, watermark, text, low quality, cartoon, anime"
}'
Video Prompting
Basic Structure
[Shot Type] + [Subject] + [Action] + [Setting] + [Style]
Camera Movement
belt app run google/veo-3-1-fast --input '{
"prompt": "Slow tracking shot following a woman walking through a sunlit forest, golden hour lighting, shallow depth of field, cinematic, 4K"
}'
Action Description
belt app run google/veo-3-1-fast --input '{
"prompt": "Close-up of hands kneading bread dough on a wooden surface, flour dust floating in morning light, slow motion, cozy baking aesthetic"
}'
Temporal Keywords
slow motion, timelapse, real-time, smooth motion,
continuous shot, quick cuts, frozen moment
Advanced Techniques
System Prompts
belt app run openrouter/claude-sonnet-45 --input '{
"system": "You are a helpful coding assistant. Always provide code with comments. If you are unsure about something, say so rather than guessing.",
"prompt": "Write a Python function to validate email addresses using regex."
}'
Structured Output
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "Extract information from this text and return as JSON:\n\n\"John Smith, CEO of TechCorp, announced yesterday that the company raised $50 million in Series B funding. The round was led by Venture Partners.\"\n\nSchema:\n{\n \"person\": string,\n \"title\": string,\n \"company\": string,\n \"event\": string,\n \"amount\": string,\n \"investor\": string\n}"
}'
Iterative Refinement
# Start broad
belt app run falai/flux-dev --input '{
"prompt": "A castle on a hill"
}'
# Add specifics
belt app run falai/flux-dev --input '{
"prompt": "A medieval stone castle on a grassy hill"
}'
# Add style
belt app run falai/flux-dev --input '{
"prompt": "A medieval stone castle on a grassy hill, dramatic sunset sky, fantasy art style, epic composition"
}'
# Add technical
belt app run falai/flux-dev --input '{
"prompt": "A medieval stone castle on a grassy hill, dramatic sunset sky, fantasy art style by Greg Rutkowski, epic composition, 8K, highly detailed"
}'
Multi-Turn Reasoning
# First: analyze
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "Analyze this business problem: Our e-commerce site has a 70% cart abandonment rate. List potential causes."
}'
# Second: prioritize
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "Given these causes of cart abandonment: [previous output], rank them by likely impact and ease of fixing. Format as a priority matrix."
}'
# Third: action plan
belt app run openrouter/claude-sonnet-45 --input '{
"prompt": "For the top 3 causes identified, provide specific A/B tests we can run to validate and fix each issue."
}'
Model-Specific Tips
Claude
- Excels at nuanced instructions
- Responds well to role-playing
- Good at following complex constraints
- Prefers explicit output formats
GPT-4
- Strong at code generation
- Works well with examples
- Good structured output
- Responds to "let's think step by step"
FLUX
- Detailed subject descriptions
- Style references work well
- Lighting keywords important
- Negative prompts supported
Veo
- Camera movement keywords
- Cinematic language works well
- Action descriptions important
- Include temporal context
Common Mistakes
| Mistake | Problem | Fix |
|---|---|---|
| Too vague | Unpredictable output | Add specifics |
| Too long | Model loses focus | Prioritize key info |
| Conflicting | Confuses model | Remove contradictions |
| No format | Inconsistent output | Specify format |
| No examples | Unclear expectations | Add few-shot |
Prompt Templates
Code Review
Review this [language] code for:
1. Bugs and logic errors
2. Security vulnerabilities
3. Performance issues
4. Code style/best practices
Code:
[code]
For each issue found, provide:
- Line number
- Issue description
- Severity (high/medium/low)
- Suggested fix
Content Writing
Write a [content type] about [topic].
Audience: [target audience]
Tone: [formal/casual/professional]
Length: [word count]
Key points to cover:
1. [point 1]
2. [point 2]
3. [point 3]
Include: [specific elements]
Avoid: [things to exclude]
Image Generation
[Subject with details], [setting/background], [lighting type],
[art style or photography style], [composition], [quality keywords]
Related Skills
# Video prompting guide
npx skills add inference-sh/skills@video-prompting-guide
# LLM models
npx skills add inference-sh/skills@llm-models
# Image generation
npx skills add inference-sh/skills@ai-image-generation
# Full platform skill
npx skills add inference-sh/skills@infsh-cli
Browse all apps: belt app list
FAQ
What does the prompt-engineering skill do?
Master prompt engineering for AI models: LLMs, image generators, video models. Techniques: chain-of-thought, few-shot, system prompts, negative prompts. Models: Claude, GPT-4, Gemini, FLUX, Veo, Stable Diffusion prompting. Use for: better AI outputs, consistent results, complex tasks, optimization. Triggers: prompt engineering, how to prompt, better prompts, prompt tips, prompting guide, llm prompting, image prompt, ai prompting, prompt optimization, prompt template, prompt structure, effective prompts, prompt techniques
How do I install prompt-engineering?
Run npx skills add https://github.com/101-skills/superpowers --skill prompt-engineering in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/prompt-engineering/ (personal) or .claude/skills/prompt-engineering/ (project).
Which AI agents can use prompt-engineering?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is prompt-engineering safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains prompt-engineering?
It is published by 101-skills in 101-skills/superpowers. It has 152 recorded installs.
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