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 ThinkingQuestioning ApproachExamplePointWhat's the core viewpoint?"What's the core viewpoint you want to express?"ReasonWhy do you think so?"Why do you think so? What's the reason?"WhatWhat specifically?"What does this specifically refer to?"WhyWhy is it important?"What pain point does it solve?"HowHow is it done?"How is it implemented?"ExampleAny examples?"Any specific cases?"SituationInitial state?"What was the initial state?"ComplicationWhat 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:

KeywordsRecommended FrameworkWhy, essence, original intention, mission, valueGolden CircleProblem, challenge, dilemma, turning point, storySCQAPromotion, publicity, conversion, sales, marketingAIDAViewpoint, opinion, think, should, suggestPREPDeep dive, root cause, trace back, underlying5-WhyInnovation, breakthrough, disrupt, reconstruct, essenceFirst PrinciplesProduct, feature, advantage, selling point, characteristicFBAOther or unclear5W1H (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

StageSearch FocusExample KeywordsInitial searchBackground info, basic facts"Qianwen 3 release", "AI e-commerce assistant"Precision searchUser unique viewpoint validation"AI vs e-commerce conflict", "traffic distribution AI impact"Comparison searchInternational 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)

DimensionCheck ItemDescriptionCore ViewpointIs the core viewpoint to be expressed clear?The soul of the articleTarget AudienceIs it clear who it's written for?Determines expression stylePublishing PlatformIs it clear where to publish?Determines content formatReal CasesAre there specific examples/experiences?Social media required****Emotional ResonanceAre there resonance points/emotional hooks?Social media required****Unique ViewpointsAre there insights others haven't mentioned?90+ point required

Should Be Complete (Try to question)

DimensionCheck ItemDescriptionExternal ValidationIs there search material to support?Adds persuasiveness

Nice to Have (Better if present)

DimensionCheck ItemDescriptionInteractive DesignIs there a clear call to action?Guide reader participationStyle PreferenceWhat style?Professional/humorous/story-based

---

90+ Point Content Standards#

ScoreCharacteristicsWhat's Missing60-70 pointsClear structure, clear viewpointsLacks real cases, emotional resonance80-85 points+ Real cases, emotional resonanceLacks uniqueness, external validation90+ points+ Unique viewpoints, external validationNothing 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 ElementUse CaseExampleHeading LevelsMain title H1, sections H2-H4# Title ## SectionBold EmphasisCore viewpoints, keywords**Core viewpoint**Quote BlocksGolden sentences, key assertions> Quote contentListsParallel points, step descriptions- Item 1Horizontal RulesSeparate different parts---Code BlocksTechnical 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#

PlatformWord CountCharacteristicsWeChat Official Account2000+In-depth long articles, clear sections, image suggestionsXiaohongshu500-1000Practical content, emoji embellishment, list-styleTwitter/Weibo140-280Concise and powerful, one-sentence core, golden sentence styleLinkedIn/Maimai1000-1500Professional 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 TypeExamplesAcademic ResourcesarXiv, Google Scholar, CNKIIndustry ReportsMcKinsey, Gartner, iResearchProfessional TechnicalOfficial docs, tech blogs, GitHubNews MediaCaixin, 36Kr, TechCrunchKnowledge PlatformsWikipedia, 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