Question Answering Skill
General-purpose question answering capability powered by OpenRouter.
Access 300+ LLM models (GPT-4o, Claude, Llama, Gemini, Mistral, etc.) through a single unified API.
Handles conversational queries, explanations, code generation, analysis, and creative writing.
Capabilities
Conversational Q&A
- Direct question answering with contextual understanding
- Multi-turn conversation with history awareness
- Follow-up questions and clarification handling
Code Assistance
- Code generation in multiple languages
- Code explanation and debugging
- Architecture and design pattern suggestions
Analysis and Reasoning
- Data interpretation and summarization
- Comparative analysis
- Logical reasoning and problem solving
Creative Writing
- Content generation (articles, emails, documentation)
- Tone adaptation (formal, casual, technical)
- Multi-language support
Supported Models (via OpenRouter)
| Provider |
Models |
Strengths |
| OpenAI |
GPT-4o, GPT-4o-mini |
General purpose, fast |
| Anthropic |
Claude Sonnet, Claude Haiku |
Analysis, safety, long context |
| Meta |
Llama 3.1 70B/405B |
Open source, multilingual |
| Google |
Gemini 2.0 Flash |
Multimodal, fast |
| Mistral |
Mistral Large, Codestral |
European, code-focused |
Examples
- "Explain how microservices work"
- "What are the pros and cons of GraphQL vs REST?"
- "Help me understand async/await in TypeScript"
- "Write a Python function to parse CSV files"
- "Compare PostgreSQL and MongoDB for my use case"
- "Summarize the key points of this document"
Performance
| Metric |
Value |
| Average response time |
1-5s (model dependent) |
| Max concurrent requests |
10 |
| Context window |
Up to 128k tokens (model dependent) |
| Supported languages |
50+ natural languages |
Requirements
When to Use
- General knowledge questions
- Code assistance and review
- Content generation and editing
- Data analysis and interpretation
- Conversational AI applications
When NOT to Use
- Real-time data (stock prices, live sports) - use a web search agent
- Image generation - use a DALL-E or Stable Diffusion agent
- File processing (PDF, Excel) - use a document processing agent
- Database queries - use a data agent with direct DB access
Integration
This skill is used by the TypeScript OpenRouter agent example:
bindufy({
skills: ["skills/question-answering"],
}, async (messages) => {
const response = await openrouter.chat.completions.create({
model: "openai/gpt-4o",
messages: messages,
});
return response.choices[0].message.content;
});
Assessment
Keywords
question, answer, explain, help, how, what, why, write, generate, analyze, summarize, compare, code, debug
Specializations
- domain: general_knowledge (confidence_boost: 0.2)
- domain: code_assistance (confidence_boost: 0.3)
- domain: content_generation (confidence_boost: 0.2)
Complexity Indicators
- Simple: "what is", "explain", "define", single-topic questions
- Medium: "compare", "analyze", multi-step reasoning
- Complex: "design a system", "debug this code", multi-domain synthesis
1---2name: question-answering3description: Question Answering Skill4---56# Question Answering Skill78General-purpose question answering capability powered by OpenRouter.9Access 300+ LLM models (GPT-4o, Claude, Llama, Gemini, Mistral, etc.) through a single unified API.10Handles conversational queries, explanations, code generation, analysis, and creative writing.1112## Capabilities1314### Conversational Q&A15- Direct question answering with contextual understanding16- Multi-turn conversation with history awareness17- Follow-up questions and clarification handling1819### Code Assistance20- Code generation in multiple languages21- Code explanation and debugging22- Architecture and design pattern suggestions2324### Analysis and Reasoning25- Data interpretation and summarization26- Comparative analysis27- Logical reasoning and problem solving2829### Creative Writing30- Content generation (articles, emails, documentation)31- Tone adaptation (formal, casual, technical)32- Multi-language support3334## Supported Models (via OpenRouter)3536| Provider | Models | Strengths |37|----------|--------|-----------|38| OpenAI | GPT-4o, GPT-4o-mini | General purpose, fast |39| Anthropic | Claude Sonnet, Claude Haiku | Analysis, safety, long context |40| Meta | Llama 3.1 70B/405B | Open source, multilingual |41| Google | Gemini 2.0 Flash | Multimodal, fast |42| Mistral | Mistral Large, Codestral | European, code-focused |4344## Examples4546- "Explain how microservices work"47- "What are the pros and cons of GraphQL vs REST?"48- "Help me understand async/await in TypeScript"49- "Write a Python function to parse CSV files"50- "Compare PostgreSQL and MongoDB for my use case"51- "Summarize the key points of this document"5253## Performance5455| Metric | Value |56|--------|-------|57| Average response time | 1-5s (model dependent) |58| Max concurrent requests | 10 |59| Context window | Up to 128k tokens (model dependent) |60| Supported languages | 50+ natural languages |6162## Requirements6364- OpenRouter API key (get one at https://openrouter.ai/keys)65- Internet connection for API calls6667## When to Use6869- General knowledge questions70- Code assistance and review71- Content generation and editing72- Data analysis and interpretation73- Conversational AI applications7475## When NOT to Use7677- Real-time data (stock prices, live sports) - use a web search agent78- Image generation - use a DALL-E or Stable Diffusion agent79- File processing (PDF, Excel) - use a document processing agent80- Database queries - use a data agent with direct DB access8182## Integration8384This skill is used by the TypeScript OpenRouter agent example:8586```typescript87bindufy({88 skills: ["skills/question-answering"],89}, async (messages) => {90 const response = await openrouter.chat.completions.create({91 model: "openai/gpt-4o",92 messages: messages,93 });94 return response.choices[0].message.content;95});96```9798## Assessment99100### Keywords101question, answer, explain, help, how, what, why, write, generate, analyze, summarize, compare, code, debug102103### Specializations104- domain: general_knowledge (confidence_boost: 0.2)105- domain: code_assistance (confidence_boost: 0.3)106- domain: content_generation (confidence_boost: 0.2)107108### Complexity Indicators109- Simple: "what is", "explain", "define", single-topic questions110- Medium: "compare", "analyze", multi-step reasoning111- Complex: "design a system", "debug this code", multi-domain synthesis