Skill: nwcalvin/innotech-poe-api (version 1.0.0)

# Poe API Orchestration Skill **Purpose**: Enable OpenClaw to intelligently query multiple AI models via Poe API **Version**: 1.0.0 **Last Updated**: 2026-03-03 --- ## What This Skill Does This skill provides: 1. **Intelligent Model Selection** - Automatically choose the right AI model for each task 2. **Poe API Integration** - Simple interface to query 300+ AI models 3. **Task-Based Routing** - Route requests to the best model based on task type 4. **Cost Optimization** - Use appropriate models to balance quality and cost --- ## When OpenClaw Should Use This Skill Use this skill when you need to: - ✅ Query AI models for text generation, reasoning, or analysis - ✅ Generate images, videos, or audio - ✅ Perform web searches with AI assistance - ✅ Access specialized models for specific tasks - ✅ Need to choose between multiple AI models **Do NOT use this skill for**: - Simple string operations (use built-in functions) - Local file operations - System commands --- ## Quick Start ### 1. Read the Model Selection Guide **CRITICAL**: Before using this skill, read: ``` MODEL_SELECTION_GUIDE.md ``` This guide teaches you: - Which model to use for each task type - When to use Claude, GPT, Gemini, or other models - How to balance quality, speed, and cost ### 2. Use the Client ```python from skills.poe_api.scripts.poe_client import PoeClient # Initialize client = PoeClient() # Simple query (auto-selects best model) result = client.query_for_task( task_type="programming", message="Write a Python function to sort a list" ) # Specific model result = client.query("claude-sonnet-4.6", "Your prompt") # Web search result = client.web_search("Latest AI developments") # Generate image result = client.generate_image("A sunset over mountains") # Generate video result = client.generate_video("A cat playing piano") ``` --- ## Task Types and Model Selection ### **Text/Reasoning Tasks** | Task Type | Primary Model | When to Use | |-----------|---------------|-------------| | **Programming** | claude-sonnet-4.6 | General coding, algorithms | | **Complex Problems** | claude-opus-4.6 | Deep reasoning, architecture | | **Fast/Cheap** | claude-haiku-4.5 | Quick tasks, simple code | | **Huge Context** | gemini-3.1-pro | >200K tokens, design systems | | **Code-Focused** | gpt-5.3-codex | Debugging, code completion | | **UI/UX Design** | gemini-3.1-pro | Design systems, UX research | | **Requirements** | claude-sonnet-4.6 | Gathering, analysis | | **Data Analysis** | claude-sonnet-4.6 | Data interpretation | ### **Web Search Tasks** | Task Type | Model | When to Use | |-----------|-------|-------------| | **Simple Search** | perplexity-search | Quick lookups | | **Complex Queries** | perplexity-sonar-pro | In-depth research | | **Reasoning + Search** | perplexity-sonar-rsn-pro | Analysis with sources | | **Deep Research** | o3-deep-research | Extensive research | | **Budget Research** | o4-mini-deep-research | Cost-conscious | ### **Image Generation** | Task Type | Model | When to Use | |-----------|-------|-------------| | **Best Quality** | imagen-4-ultra | Professional graphics | | **Fast + Good** | nano-banana-2 | Quick iterations | | **Text in Images** | nano-banana-pro | Banners, signs | | **General Purpose** | nano-banana | Standard generation | | **Professional Editing** | gpt-image-1.5 | Complex edits | | **Asian Aesthetics** | seedream-4.0 | Specific style | ### **Video Generation** | Task Type | Model | When to Use | |-----------|-------|-------------| | **Best + Audio** | veo-3.1 | Cinematic with sound | | **Cinematic** | sora-2-pro | High-fidelity | | **Versatile** | kling-o3 | Multiple workflows | | **Standard** | sora-2 | Good quality | | **Storytelling** | wan-2.6 | Multi-scene | | **Fast** | seedance-1.0-pro | Quick generation | ### **Audio Generation** | Task Type | Model | When to Use | |-----------|-------|-------------| | **Realistic Speech** | elevenlabs-v3 | Audiobooks, podcasts | | **Fast TTS** | gemini-2.5-flash-tts | Quick conversion | | **Controlled Speech** | hailuo-speech-02 | Fine-grained control | | **Music** | hailuo-music-v1.5 | Song generation | --- ## Key Principles ### 1. **Read MODEL_SELECTION_GUIDE.md First** This guide contains: - Detailed decision trees - Model capabilities and strengths - When to use each model - Cost/quality tradeoffs ### 2. **Default to claude-sonnet-4.6** When in doubt, use `claude-sonnet-4.6`: - Best all-around performance - 983K token context - Excellent at most tasks - Good balance of speed and quality ### 3. **Use Task-Based Methods** Instead of manually selecting models, use: ```python # Automatic model selection client.query_for_task(task_type="programming", message="...") client.query_for_task(task_type="ui_design", message="...") client.query_for_task(task_type="data_analysis", message="...") ``` ### 4. **Consider Context Size** - **< 200K tokens**: Claude-Sonnet, Claude-Opus, GPT models - **> 200K tokens**: Gemini-3.1-Pro (1M context) ### 5. **Balance Quality vs Speed** - **Highest Quality**: claude-opus-4.6, imagen-4-ultra, veo-3.1 - **Balanced**: claude-sonnet-4.6, nano-banana-2 - **Fast/Cheap**: claude-haiku-4.5, perplexity-search --- ## Model Capabilities ### **Text Models** #### **Claude Family (Anthropic)** - **claude-opus-4.6**: 983K context, deepest reasoning - **claude-sonnet-4.6**: 983K context, best all-around - **claude-haiku-4.5**: 192K context, fastest **Strengths**: - Excellent reasoning and coding - Great at following complex instructions - Strong safety and reliability - Very large context windows #### **GPT Family (OpenAI)** - **gpt-5.3-codex**: 400K context, code-focused - **gpt-5.2**: 400K context, general purpose **Strengths**: - Great at code completion - Good instruction following - Large context #### **Gemini Family (Google)** - **gemini-3.1-pro**: **1M context**, multimodal **Strengths**: - Massive 1M token context - Multimodal input (text, image, video, audio) - Great for design systems ### **Search Models (Perplexity)** - **perplexity-search**: Simple web search - **perplexity-sonar-pro**: Complex queries with citations - **perplexity-sonar-rsn-pro**: Reasoning + search **Strengths**: - Real-time web access - Citations included - Great for research ### **Image Models** - **imagen-4-ultra**: Best quality - **nano-banana-2**: Latest, fast, 4K - **gpt-image-1.5**: Professional editing ### **Video Models** - **veo-3.1**: Best quality + native audio - **sora-2-pro**: Cinematic (OpenAI) - **kling-o3**: Most versatile (4 workflows) ### **Audio Models** - **elevenlabs-v3**: Most realistic speech - **hailuo-music-v1.5**: Music generation --- ## Common Use Cases ### **Programming Tasks** ```python # General coding result = client.query_for_task( task_type="programming", message="Write a REST API in Python" ) # Code review result = client.query_for_task( task_type="programming", message=f"Review this code: {code}" ) # Debugging result = client.query_for_task( task_type="programming", message=f"Debug this error: {error}" ) ``` ### **UI/UX Design** ```python # Design system result = client.query_for_task( task_type="ui_design", message="Create a design system for a fintech app" ) # User research result = client.query_for_task( task_type="ui_design", message="Analyze user flow for checkout process" ) ``` ### **Data Analysis** ```python # Analyze data result = client.query_for_task( task_type="data_analysis", message=f"Analyze this dataset: {data}" ) # Generate insights result = client.query_for_task( task_type="data_analysis", message="What trends do you see in this data?" ) ``` ### **Web Search** ```python # Quick search result = client.web_search("Latest AI developments 2026") # Deep research result = client.deep_search( "Impact of AI on job markets", model="o3-deep-research" ) ``` ### **Content Creation** ```python # Generate image result = client.generate_image( "Modern dashboard UI with dark theme" ) # Generate video result = client.generate_video( "A drone shot of city skyline at sunset" ) # Generate audio result = client.generate_audio( "[whispers] Welcome to our podcast", voice_model="elevenlabs-v3" ) ``` --- ## Decision Framework ### **Step 1: Identify Task Type** Ask yourself: - Is this programming? → `programming` - Is this design? → `ui_design` - Is this analysis? → `data_analysis` - Is this search? → `web_search` - Is this creative? → `image/video/audio` ### **Step 2: Check Context Size** - **< 200K tokens**: Any Claude/GPT model - **> 200K tokens**: Must use `gemini-3.1-pro` ### **Step 3: Balance Quality vs Speed** - **Need best quality?** → Use Pro/Ultra models - **Need fast?** → Use Haiku/Flash models - **Need balanced?** → Use Sonnet/Standard models ### **Step 4: Use Task-Based Methods** ```python # Let the skill choose the model result = client.query_for_task( task_type="programming", message="Your task", complexity="medium" # low, medium, high ) ``` --- ## Important Notes ### **Token Limits** - **Managed by Poe API** - No need to specify - Different models have different limits - Poe will automatically handle limits ### **Cost Management** - Use `max_calls_per_task` to limit API calls - Use cheaper models for simple tasks - Reserve expensive models for complex work ### **Error Handling** - Always check `result["success"]` - Implement retry logic - Use fallback models if primary fails --- ## Examples See `examples/` directory for: - Basic usage examples - Advanced workflows - Error handling patterns - Multi-step tasks --- ## Troubleshooting ### **Model Not Available** ``` Error: Model not found ``` **Solution**: Model names are case-sensitive. Use lowercase: - ✅ `claude-sonnet-4.6` - ❌ `Claude-Sonnet-4.6` ### **Rate Limited** ``` Error: Rate limit exceeded ``` **Solution**: Wait and retry, or use fallback model ### **Context Too Large** ``` Error: Context exceeds limit ``` **Solution**: Use `gemini-3.1-pro` (1M context) --- ## Next Steps 1. ✅ Read `MODEL_SELECTION_GUIDE.md` for detailed model information 2. ✅ Check `examples/` for usage patterns 3. ✅ Use `query_for_task()` for automatic model selection 4. ✅ When in doubt, use `claude-sonnet-4.6` --- **Remember**: The key to using this skill effectively is understanding which model to use for which task. Read `MODEL_SELECTION_GUIDE.md` carefully! 🎯

path: requirements.txt
content: openai>=1.0.0


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