guides/prompting/prompt-engineering/SKILL.md
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
npx skillsauth add inference-sh/agent-skills prompt-engineeringInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Master prompt engineering for AI models via inference.sh CLI.

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."
}'
[Role/Context] + [Task] + [Constraints] + [Output Format]
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."
}'
# 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."
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."
}'
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?"
}'
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."
}'
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]"
}'
[Subject] + [Style] + [Composition] + [Lighting] + [Technical]
# 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"
}'
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"
}'
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"
}'
photorealistic, 8K, ultra detailed, sharp focus, professional,
masterpiece, high quality, best quality, intricate details
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"
}'
[Shot Type] + [Subject] + [Action] + [Setting] + [Style]
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"
}'
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"
}'
slow motion, timelapse, real-time, smooth motion,
continuous shot, quick cuts, frozen moment
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."
}'
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}"
}'
# 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"
}'
# 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."
}'
| 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 |
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
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]
[Subject with details], [setting/background], [lighting type],
[art style or photography style], [composition], [quality keywords]
# 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
development
Render videos from React/Remotion component code via inference.sh. Pass TSX code, get MP4. Supports all Remotion APIs: useCurrentFrame, useVideoConfig, spring, interpolate, AbsoluteFill, Sequence. Configurable resolution, FPS, duration, codec. Use for: programmatic video generation, animated graphics, motion design, data-driven videos, React animations to video. Triggers: remotion, render video from code, tsx to video, react video, programmatic video, remotion render, code to video, animated video, motion graphics code, react animation video
tools
Generate videos with Pruna P-Video and WAN models via inference.sh CLI. Models: P-Video, WAN-T2V, WAN-I2V. Capabilities: text-to-video, image-to-video, audio support, 720p/1080p, fast inference. Pruna optimizes models for speed without quality loss. Triggers: pruna video, p-video, pruna ai video, fast video generation, optimized video, wan t2v, wan i2v, economic video generation, cheap video generation, pruna text to video, pruna image to video
documentation
Still-to-video conversion guide: model selection, motion prompting, and camera movement. Covers Wan 2.5 i2v, Seedance, Fabric, Grok Video with when to use each. Use for: animating images, creating video from stills, adding motion, product animations. Triggers: image to video, i2v, animate image, still to video, add motion to image, image animation, photo to video, animate still, wan i2v, image2video, bring image to life, animate photo, motion from image
tools
Generate videos with Google Veo models via inference.sh CLI. Models: Veo 3.1, Veo 3.1 Fast, Veo 3, Veo 3 Fast, Veo 2. Capabilities: text-to-video, cinematic output, high quality video generation. Triggers: veo, google veo, veo 3, veo 2, veo 3.1, vertex ai video, google video generation, google video ai, veo model, veo video