Skill: okaris/prompt-engineering (version 0.1.5)

--- name: prompt-engineering description: "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" allowed-tools: Bash(infsh *) --- # Prompt Engineering Guide Master prompt engineering for AI models via [inference.sh](https://inference.sh) CLI. ![Prompt Engineering Guide](https://cloud.inference.sh/app/files/u/4mg21r6ta37mpaz6ktzwtt8krr/01kgvftjwhby36trvaj66bwzcf.jpeg) ## Quick Start ```bash curl -fsSL https://cli.inference.sh | sh && infsh login # Well-structured LLM prompt infsh 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." }' ``` > **Install note:** The [install script](https://cli.inference.sh) only detects your OS/architecture, downloads the matching binary from `dist.inference.sh`, and verifies its SHA-256 checksum. No elevated permissions or background processes. [Manual install & verification](https://dist.inference.sh/cli/checksums.txt) available. ## LLM Prompting ### Basic Structure ``` [Role/Context] + [Task] + [Constraints] + [Output Format] ``` ### Role Prompting ```bash infsh 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 ```bash # 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 ```bash infsh 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 ```bash infsh 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 ```bash infsh 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 ```bash infsh 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 ```bash # Bad: vague "a cat" # Good: specific infsh app run falai/flux-dev --input '{ "prompt": "A fluffy orange tabby cat with green eyes, sitting on a vintage leather armchair" }' ``` ### Style Keywords ```bash infsh 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 ```bash infsh 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 ```bash infsh 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 ```bash infsh 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 ```bash infsh 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 ```bash infsh 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 ```bash infsh 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 ```bash # Start broad infsh app run falai/flux-dev --input '{ "prompt": "A castle on a hill" }' # Add specifics infsh app run falai/flux-dev --input '{ "prompt": "A medieval stone castle on a grassy hill" }' # Add style infsh 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 infsh 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 ```bash # First: analyze infsh 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 infsh 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 infsh 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 ```bash # 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@inference-sh ``` Browse all apps: `infsh app list`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)