Personal Material Library Search

When to Use This Skill

• Needs "real experience", "personal case", "practical experience"
• Wants content to be "well-founded", "more credible", "authentic"
• Mentions "material library", "looking for examples", "looking for cases"
• Wants to "increase persuasiveness", "be more convincing"
• Needs specific data or supporting materials

Core Objectives

Execution Process

Step 1: Understand Search Requirements

1. Topic Keyword Extraction
   • Extract core concepts and keywords
   • Identify industry fields and professional directions
   • Analyze user intent (case/data/opinion)
2. Material Type Judgment
   • 📊 Data-type material: Specific numbers, percentages, statistical information
   • 📖 Case-type material: Complete stories, project experiences, success cases
   • 💡 Opinion-type material: Personal insights, industry analysis, trend judgment
   • 🔍 Detail-type material: Specific operations, tool usage, process description
3. Application Scenario Confirmation
   • Demonstrating viewpoints - need strong case support
   • Enriching content - need specific detail descriptions
   • Increasing credibility - need real data and experiences
   • Providing value - need practical experience and suggestions

Step 2: Build Search Strategy

1. Core Keywords
   • Use topic words directly: such as "product management", "user experience"
   • Use synonyms: such as "PM", "UX design" as alternatives
   • Use English terms: such as "AI", "SaaS", "KOL"
2. Combined Keywords
   • Topic + action: such as "product management" + "experience"
   • Topic + result: such as "entrepreneurship" + "success case"
   • Topic + tool: such as "data analysis" + "Excel"
3. Extended Search
   • Related fields: such as "marketing" related to "growth hacking"
   • Upstream and downstream concepts: such as "development" related to "testing"
   • Industry-wide experience: such as "Internet" related to "e-commerce"

Step 3: Execute Material Search

1. CSV Database Search
   • Use Grep tool to search in the material library file
   • Support fuzzy matching and exact matching
   • Search fields such as title, content, tags, etc.
2. Matching Degree Evaluation
   • Perfect match (90-100%): The topics are completely consistent
   • High match (70-89%): High topic relevance
   • Partial match (50-69%): Has certain reference value
   • Low match (30-49%): Only for supplementary reference
3. Multi-result Processing
   • Prioritize the 3-5 entries with the highest matching degree
   • Display sorted by relevance
   • Mark the type and applicable scenario of each material

Step 4: Material Sorting and Rewriting

1. De-identification Processing
   • Remove specific company names
   • Hide real personal name information
   • Blur specific time and location
2. Language Style Adaptation
   • Adjust the tone to match the article style
   • Maintain objectivity and avoid subjective assumptions
   • Use a unified expression method
3. Content Structure Optimization
   • Extract core viewpoints and data
   • Simplify lengthy descriptions
   • Highlight key information and value

Step 5: Provide Usage Suggestions

1. Insertion Position Suggestions
   • As support after demonstrating viewpoints
   • As cases in the example explanation part
   • As basis in the data analysis part
2. Expression Suggestions
   • Direct quotation: Keep the original meaning
   • General quotation: Extract core points
   • Comparative quotation: Form a response with the viewpoint
3. Value Point Emphasis
   • Mark the credibility level of the material
   • Point out the most persuasive points
   • Suggest how to further strengthen the effect

Material Library Structure

Database Fields

• ID: Unique identifier
• title: Material title
• content: Detailed content description
• type: Material type (case/data/opinion/detail)
• category: Classification tag
• date: Record time
• reliability: Credibility rating (1-5 points)
• usage_count: Number of uses
• notes: Remarks

Classification System

1. Professional Experience: Work, project, management experience
2. Entrepreneurial Experience: Entrepreneurship process, business model, financing experience
3. Technical Practice: Programming, product design, data analysis
4. Marketing and Operation: Marketing, promotion, user growth
5. Personal Growth: Learning, thinking, life insights

Quality Standards

• Material matching degree >= 70%
• Content authenticity has been verified
• Language is smooth and natural after processing
• Provide specific usage suggestions

Special Processing

1. No Matching Material Found

• Expand the search scope to related fields
• Provide alternative materials with similar concepts
• Suggest users to supplement relevant information

2. Overly Sensitive Materials

• Conduct sufficient information desensitization
• Retain core experience but hide specific details
• Provide generalized expression methods

3. Materials Need to Be Updated

• Mark time information and remind timeliness
• Suggest supplementing with the latest situation
• Provide the value of historical comparison

Notes

• Protect private information and conduct appropriate desensitization processing
• Ensure the timeliness and accuracy of materials
• Remain objective and neutral, avoid excessive rendering
• Provide multi-angle material selection