Idea To Post

Expand scattered ideas into in-depth posts. Use this skill when users need to "expand ideas," "generate posts," "brainstorm content," "writing assistance," "enrich thoughts," "deepen thinking," or provide scattered ideas that need systematic expression.

Idea-to-Post Expansion Skill

Skill Overview

This skill helps you expand scattered ideas (a sentence, a few words, a vague thought) into 90+ point social media posts.

Target Positioning: Quality social media content, not technical documentation

It works through the following ways:

1. Framework Internalization - Use thinking frameworks to design questions, but don't mechanically apply them
2. Information Search & Integration - Automatically search for high-quality materials, supplement relevant data and cases
3. Progressive Deep Questioning - Multiple-choice to set direction + open questions to enrich content, 7-10 rounds of dialogue until complete
4. Iterative Polishing & Optimization - Reflect and optimize after generation, pursuing 90+ point quality
5. Multi-Platform Output - Generate post versions adapted to different platforms

Expected dialogue rounds: 7-10 rounds

• 3-4 rounds: Get direction and core viewpoints (technical documentation level)
• 5-7 rounds: Add cases, emotions, uniqueness (social media level)
• 7-10 rounds: Deep mining, repeated polishing (quality social media level)

Core Mechanism: Progressive Questioning + Framework Internalization

Three Core Principles

1. Internalize Frameworks, Don't Expose Them

Use thinking framework logic to design questions, but don't say "I'm using [Framework Name]":

text

Wrong: "I recommend using the PREP framework. Now for Point: What's your viewpoint?"
Correct: "What's the core viewpoint you want to express?"

Questions have framework thinking, but the dialogue is natural.

2. Combine Multiple Choice + Open Questions

text

Multiple Choice (AskUserQuestion)  Quickly lock direction
Open Questions (direct dialogue)    Deeply mine content

Multiple Choice = Skeleton | Open Questions = Flesh and blood

3. Progressive Deepening, Dynamic Adjustment

Each round of questions is based on the previous answer, naturally transitioning to the next dimension:

text

User: "todo is an underrated command"
    ↓
Follow-up: What does "underrated" specifically mean? (Concept deepening)
    ↓
User: "People don't know it's a conversation memory mechanism"
    ↓
Follow-up: What pain point does it solve? (Value inquiry)
    ↓
Follow-up: Any specific examples? (Case supplement)

---

Questioning Flow (7-10 Rounds of Dialogue + Multi-Stage Search)

text

┌─────────────────────────────────────────────────┐
│  User inputs idea                                │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  [Initial Search] Background information        │
│  collection                                     │
│  - Identify core concepts                        │
│  - Multi-angle search queries                    │
│  - Get background materials                      │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Rounds 1-2: Direction locking                  │
│  (mainly multiple choice)                        │
│  - Goal? Audience? Platform?                     │
│  - Quickly position article type                 │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Rounds 3-4: Core deep dive                     │
│  (open questions)                                │
│  - What's the core viewpoint?                    │
│  - What does "underrated" specifically mean?     │
│  - What pain point does it solve?                │
│  - Why do you think so?                          │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Rounds 5-6: Real cases                         │
│  (open questions, required)                      │
│  - When was the most recent time?                │
│  - What feature? What specifically was said?     │
│  - How did you feel at that moment?              │
│  - Any comparison cases? (with vs without)       │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Round 7: Emotional resonance                   │
│  (open questions, required)                      │
│  - Most frustrated/surprised moment?             │
│  - Physical reaction? Slap thigh? Long sigh?     │
│  - Turning point from "useless" to "amazing"?    │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Round 8: Uniqueness                            │
│  (open questions)                                │
│  - Any undiscovered tips?                        │
│  - Any unique usage methods?                     │
│  - Any counter-intuitive understanding?          │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  [Precision Search] Based on user's unique      │
│  viewpoints                                      │
│  - Extract unique insights/counter-intuitive     │
│    viewpoints                                    │
│  - Reverse search for supporting evidence        │
│  - Multi-angle validation                        │
│    (industry/competitors/data)                   │
│  - Try different keywords if search fails        │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Round 9: Structure confirmation                │
│  (multiple choice)                               │
│  - Article structure?                            │
│  - Style preference?                             │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Round 10: Final touches                        │
│  (mixed)                                         │
│  - Core golden sentence?                         │
│  - Call to action?                               │
│  - Anything else to add?                         │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Information completeness assessment            │
│  (90+ point standard)                            │
│  Core viewpoint                                  │
│  Real cases (required)                           │
│  Emotional resonance (required)                  │
│  Unique viewpoints (required)                    │
│  External validation (search results)            │
│  → Complete, generate content                    │
│  → Incomplete, continue questioning              │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  First draft generation                         │
│  (standard Markdown format)                      │
│  - Integrate all information                     │
│  - Use heading levels, bold, quote blocks, etc.  │
│  - Generate structured content                   │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Reflection and optimization (optional)         │
│  - What's not good enough?                       │
│  - What needs supplementing?                     │
│  - Iterate and optimize                          │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Final output (standard Markdown format)        │
└─────────────────────────────────────────────────┘

Note: Cases, emotions, and uniqueness are required and cannot be skipped. The second round of precision search is a key环节.

---

Integrating Framework Thinking into Questions

Framework Thinking	Questioning Approach	Example
Point	What's the core viewpoint?	"What's the core viewpoint you want to express?"
Reason	Why do you think so?	"Why do you think so? What's the reason?"
What	What specifically?	"What does this specifically refer to?"
Why	Why is it important?	"What pain point does it solve?"
How	How is it done?	"How is it implemented?"
Example	Any examples?	"Any specific cases?"
Situation	Initial state?	"What was the initial state?"
Complication	What conflict?	"What challenge appeared?"

Frameworks are thinking tools, not questioning templates.

---

Quick Framework Selection Guide

Automatic Recommendation Rules

Based on keywords in your input, the system will automatically recommend frameworks:

Keywords	Recommended Framework
Why, essence, original intention, mission, value	Golden Circle
Problem, challenge, dilemma, turning point, story	SCQA
Promotion, publicity, conversion, sales, marketing	AIDA
Viewpoint, opinion, think, should, suggest	PREP
Deep dive, root cause, trace back, underlying	5-Why
Innovation, breakthrough, disrupt, reconstruct, essence	First Principles
Product, feature, advantage, selling point, characteristic	FBA
Other or unclear	5W1H (default)

Framework Introduction

For detailed framework explanations, refer to references/thinking-frameworks.md

---

Usage Flow

Core Flow: Keep Questioning Until Complete

text

┌─────────────────────────────────────────────────┐
│  User inputs idea                                │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  First round: Direction questions                │
│  - Keyword analysis based on topic               │
│  - Recommend thinking framework                  │
│  - Confirm target platform and audience          │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  User answers                                    │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Second round: Framework deep dive               │
│  - Ask core elements based on selected framework │
│  - Focus on 1-2 key questions per round          │
│  - Dynamically adjust subsequent questions       │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Third round: Detail supplement                  │
│  - Ask missing details based on available info   │
│  - Cases, data, emotional points, etc.           │
│  - Interactive design and call to action         │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
            ...Loop...
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Skill judges: Information completeness          │
│  assessment                                      │
│  - Is core viewpoint clear?                      │
│  - Is supporting material sufficient?            │
│  - Are emotional resonance points clear?         │
│  - Is interactive design specific?               │
│                                                 │
│  → Incomplete: Continue questioning              │
│  → Complete: Enter generation phase              │
└────────────────┬────────────────────────────────┘
                 │
                 ▼
┌─────────────────────────────────────────────────┐
│  Integrate information to generate post          │
│  - Original idea                                 │
│  - Search materials                              │
│  - User answers                                  │
│  - Framework structure                           │
└─────────────────────────────────────────────────┘

Information Search (Multi-Stage Execution, Required)

Search must be performed in multiple stages to ensure precise external validation is collected:

Stage 1: Initial Background Search (Before questioning begins)

Execute initial information search before questioning starts:

1. Identify core concepts in the topic
2. Build multi-angle search queries
3. Use WebSearch to get relevant materials
4. Use WebFetch to read key pages in depth
5. Organize search results for later use

Stage 2: Precision Deep Search (After collecting core viewpoints)

This is the most critical step - after collecting the user's core viewpoints and unique insights, you must perform a second round of precision search:

1. Build search terms based on user's unique viewpoints

   • Extract unique insights/counter-intuitive viewpoints proposed by user
   • Use these viewpoints as keywords for reverse search
   • Look for supporting or refuting evidence

2. Multi-angle validation search

   • Search industry reports, news media
   • Search competitors/international cases
   • Search data support

3. Handling search failures

   • If one search fails/is limited, try different keyword combinations
   • Use more generic or more specific search terms
   • Try English search terms for international perspective
   • Record search status, inform user (e.g., if search was restricted)

Search Keyword Strategy

Stage	Search Focus	Example Keywords
Initial search	Background info, basic facts	"Qianwen 3 release", "AI e-commerce assistant"
Precision search	User unique viewpoint validation	"AI vs e-commerce conflict", "traffic distribution AI impact"
Comparison search	International cases, competitor analysis	"ChatGPT e-commerce", "foreign AI shopping assistant"

Search results must be integrated into final content as external validation.

Even if search is limited, try multiple different keywords and inform user of search status.

Question Design Principles

1. Question Based on Topic

Questions must be closely tied to the core topic of user input, don't ask irrelevant questions.

2. Framework-Based Design

Use framework thinking to design questions, but don't say "I'm using [Framework Name]".

3. Mix Multiple Choice + Open Questions

• Multiple Choice: When there are clear options, need quick classification
• Open Questions: When need stories/experiences/emotions/details
• Mixed: After AskUserQuestion "Other" option, continue follow-up questions

4. Progressive Deepening, Dynamic Adjustment

Each round is based on the previous answer, naturally transitioning to the next dimension. Not mechanically following a template.

5. Focus on 1-2 Questions Per Round

Avoid information overload, give user thinking space.

6. Complete Information Before Stopping

Check core dimensions, question what's missing, only generate when complete.

Completeness Judgment Standards (90+ Point Target)

When judging whether information is complete, the skill checks the following dimensions:

Must Be Complete (Continue questioning if missing, cannot skip)

Dimension	Check Item	Description
Core Viewpoint	Is the core viewpoint to be expressed clear?	The soul of the article
Target Audience	Is it clear who it's written for?	Determines expression style
Publishing Platform	Is it clear where to publish?	Determines content format
Real Cases	Are there specific examples/experiences?	Social media required
Emotional Resonance	Are there resonance points/emotional hooks?	Social media required
Unique Viewpoints	Are there insights others haven't mentioned?	90+ point required

Should Be Complete (Try to question)

Dimension	Check Item	Description
External Validation	Is there search material to support?	Adds persuasiveness

Nice to Have (Better if present)

Dimension	Check Item	Description
Interactive Design	Is there a clear call to action?	Guide reader participation
Style Preference	What style?	Professional/humorous/story-based

---

90+ Point Content Standards

Score	Characteristics	What's Missing
60-70 points	Clear structure, clear viewpoints	Lacks real cases, emotional resonance
80-85 points	+ Real cases, emotional resonance	Lacks uniqueness, external validation
90+ points	+ Unique viewpoints, external validation	Nothing missing, polished

Only enter generation phase when all "must complete" dimensions are present.

Real cases, emotional resonance, and unique viewpoints are the three pillars of social media content - all are essential.

---

Output Format

Markdown Format Specifications (Required)

All post content must be output in standard Markdown format, including:

Format Element	Use Case	Example
Heading Levels	Main title H1, sections H2-H4	# Title ## Section
Bold Emphasis	Core viewpoints, keywords	**Core viewpoint**
Quote Blocks	Golden sentences, key assertions	> Quote content
Lists	Parallel points, step descriptions	- Item 1
Horizontal Rules	Separate different parts	---
Code Blocks	Technical content, data	```code```

Pre-output checklist:

• Clear heading levels (H1 main title, H2 sections, H3 subsections)
• Bold emphasis on core viewpoints
• Quote blocks for golden sentences/key assertions
• Long content in bullet points
• Horizontal rules between sections
• Overall format follows standard Markdown syntax

Universal Structure

markdown

# [Main Title] Engaging title based on core viewpoint

## [Hook] Attention-grabbing opening

Body content...

---

## [Body Part 1] Expand based on framework structure

- Framework-guided hierarchical content
- Search data-supported viewpoints
- Specific cases and stories

> Core golden sentence in quote block

---

## [Body Part 2] Continue expansion

More content...

---

## [Conclusion] Call to action or summary reinforcement

Concluding content...

---

**[Tags]** #topic1 #topic2 #topic3

**[Reference Materials]** Data sources cited (if search was used)

Platform-Adapted Versions

Platform	Word Count	Characteristics
WeChat Official Account	2000+	In-depth long articles, clear sections, image suggestions
Xiaohongshu	500-1000	Practical content, emoji embellishment, list-style
Twitter/Weibo	140-280	Concise and powerful, one-sentence core, golden sentence style
LinkedIn/Maimai	1000-1500	Professional workplace, industry insights, case support

For detailed structure explanations, refer to references/post-structures.md

---

High-Quality Information Sources

The system prioritizes the following types of high-quality sources when searching:

Source Type	Examples
Academic Resources	arXiv, Google Scholar, CNKI
Industry Reports	McKinsey, Gartner, iResearch
Professional Technical	Official docs, tech blogs, GitHub
News Media	Caixin, 36Kr, TechCrunch
Knowledge Platforms	Wikipedia, Zhihu high-voted, Medium

For detailed data source lists, refer to references/data-sources.md

---

Best Practices

1. Provide sufficient context - Even for scattered ideas, try to include key points you care about
2. Answer questions honestly - Your answers during interactive questioning directly affect post quality
3. Define target platform - Knowing which platform you're posting to can generate more suitable content
4. Leverage search results - Materials searched by the system can greatly enrich your content
5. Compare multiple versions - Compare outputs from different versions, choose the most suitable
6. Iterate and optimize - Continue questioning and optimizing based on generated results

---

Examples

See examples/ directory for complete usage examples:

• basic-usage.md - Basic usage examples
• advanced-usage.md - Advanced scenario examples

---

Reference Documents

• references/thinking-frameworks.md - Detailed framework explanations
• references/questioning-strategy.md - Continuous progressive questioning strategy (core)
• references/questioning-modes.md - Questioning mode selection guide (new)
• references/question-templates.md - Question template library
• references/post-structures.md - Post structure guide
• references/data-sources.md - High-quality data source list