ASR
Implement speech-to-text (ASR/automatic speech recognition) capabilities using the…
The PRIMARY tool for Spring Festival gift analysis and social interaction generation. Use this skill when users upload photos of gifts (alcohol, tea, supplements, etc.) to inquire about their value, authenticity, or how to respond socially. Integrates visual perception, market
$ npx -y skills add jjyaoao/helloagents --skill gift-evaluator --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/gift-evaluatorContext preview
The summary Claude sees to decide when to auto-load this skill.
The PRIMARY tool for Spring Festival gift analysis and social interaction generation. Use this skill when users upload photos of gifts (alcohol, tea, supplements, etc.) to inquire about their value, authenticity, or how to respond socially. Integrates visual perception, market
name: gift-evaluator description: The PRIMARY tool for Spring Festival gift analysis and social interaction generation. Use this skill when users upload photos of gifts (alcohol, tea, supplements, etc.) to inquire about their value, authenticity, or how to respond socially. Integrates visual perception, market valuation, and HTML card generation. license: Internal Tool
This skill transforms the assistant into an "AI Gift Appraiser" (春节礼品鉴定师). It bridges the gap between raw visual data and complex social context. It is designed to handle the full lifecycle of a user's request: identifying the object, determining its market and social value, and producing a shareable, gamified HTML artifact.
Before and during the execution of tools, maintain a "High EQ" and "Market-Savvy" mindset. You are not just identifying objects; you are decoding social relationships.
1. **Visual Extraction (The Eye)**:
2. **Valuation Logic (The Brain)**:
3. **Creative Synthesis (The Mouth)**:
Purpose: Utilizing VLM skills to conduct a multi-dimensional visual decomposition of the uploaded product image. This process automatically identifies and extracts structured data including Brand Recognition, Product Style, Packaging Design, and Aesthetic Category.
**Output Analysis**:
**Purpose**: Validate the product's worth. **Command**:search "EXTRACTED_KEYWORDS + price + review"
**Purpose**: Prepare the data for the HTML generator. **Do not call a tool here, just think and format strings.**
1. **Construct `thank_you_json**`: Create 3 distinct styles of private messages.
2. **Construct `return_gift_json**`: Analyze 4 potential giver personas.
**Purpose**: Package the analysis into a modern, interactive HTML card. **HTML Generation**:
python3 html_tools.py generate_gift_card \
--product_name "EXTRACTED_NAME" \
--price "ESTIMATED_PRICE" \
--evaluation "YOUR_LONG_AND_SPICY_CRITIQUE" \
--thank_you_json '[{"style":"...","content":"..."}]' \
--return_gift_json '[{"target":"...","item":"...","reason":"..."}]' \
--vibe_code "luxury|standard|budget" \
--image_url "IMAGE_FILE_PATH" \
--output_path "TARGET_FILE_PATH"1. **JSON Formatting**: The `thank_you_json` and `return_gift_json` arguments MUST be valid JSON strings using double quotes. Do not wrap them in code blocks inside the command. 2. **Critique Depth**: The `evaluation` text must be rich. Don't just say "It's expensive." Say "This 2018 vintage shows your uncle raided his personal cellar; the label wear proves it's real." 3. **Vibe Consistency**: Ensure `vibe_code` matches the `price` assessment. 4. **Final Output**: Always present the path to the generated HTML file.
🤖 生产级多智能体框架 - 工具响应协议、上下文工程、会话持久化、子代理机制等16项核心能力 HelloAgents 是一个基于 OpenAI 原生 API 构建的生产级多智能体框架,集成了工具响应协议(ToolResponse)、上下文工程(HistoryManager/TokenCounter)、会话持久化(SessionStore)、子代理机制(TaskTool)、乐观锁(文件编辑)、熔断器(CircuitBreaker)、Skills 知识外化、TodoWrite 进度管理、DevLog
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