x-mentor-skill-nuwa

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

X导师.skill (X Mentor Skill)

X导师.skill (X导师Skill)

Skill by ara.so — Daily 2026 Skills collection.

A Claude Code skill that distills methodologies from 6 top X creators (Nicolas Cole, Dickie Bush, Sahil Bloom, Justin Welsh, Dan Koe, Alex Hormozi) plus open-source X algorithm data into a complete content operating system. Covers hook engineering, thread writing, growth mechanics, account diagnostics, and monetization strategy.

Skill由 ara.so 开发 — 2026年度每日Skill合集。

这是一款Claude Code Skill，萃取了6位X平台顶级创作者（Nicolas Cole、Dickie Bush、Sahil Bloom、Justin Welsh、Dan Koe、Alex Hormozi）的方法论，结合X开源算法数据，形成了完整的内容运营体系，涵盖钩子设计、thread创作、增长机制、账号诊断和变现策略等模块。

Installation

安装

bash

npx skills add alchaincyf/x-mentor-skill

After installation, activate with natural language:

"帮我写条推文"
"X策略"
"推特怎么涨粉"
"帮我审阅这条tweet"
"分析我的X账号 @username"

bash

npx skills add alchaincyf/x-mentor-skill

安装完成后，可使用自然语言激活：

"帮我写条推文"
"X策略"
"推特怎么涨粉"
"帮我审阅这条tweet"
"分析我的X账号 @username"

Five Core Scenarios

五大核心场景

Scenario A — Write a Tweet

场景A — 撰写推文

Trigger: Any request to write/create a tweet or thread.

Workflow:

Clarify format (short tweet vs. thread) and target audience
Generate 3 hook variants with formula labels
Recommend best version with rationale
Flag algorithm risks (external links, timing)

Example interaction:

User: Write a tweet about building an AI coding assistant with Claude Code

X导师: Format — short tweet or thread? Target audience?

User: Short tweet, for AI developers

X导师: 3 Hook versions:

Version A (Curiosity Gap + Credibility Anchor):
"I built an AI coding assistant with Claude Code.
48 hours. Zero frameworks. Pure vibe coding.
The surprising part wasn't that it worked — it was 3x faster than my handwritten version."

Version B (Value Equation: High Result / Low Effort):
"Can't code? Doesn't matter.
I just built an AI coding assistant in 2 days using Claude Code.
Wrote zero lines of code myself. Full walkthrough:"

Version C (Contrarian + Specific Data):
"Most AI coding assistant benchmarks are demo-level.
I built one that's actually in production using Claude Code.
The difference? 30 edge cases and an AI willing to debug until 3am."

→ Recommend Version A: has specific numbers (48h/3x) and a suspense hook.
→ Best publish time: Weekdays 9–11am.
⚠️ No external links in the post body — put them in the first reply.

触发条件：任何撰写/创作推文或thread的请求。

工作流：

明确内容形式（短推文/thread）和目标受众
生成3个带公式标签的钩子变体
推荐最优版本并说明理由
标注算法风险（外部链接、发布时机）

交互示例：

User: Write a tweet about building an AI coding assistant with Claude Code

X导师: Format — short tweet or thread? Target audience?

User: Short tweet, for AI developers

X导师: 3 Hook versions:

Version A (Curiosity Gap + Credibility Anchor):
"I built an AI coding assistant with Claude Code.
48 hours. Zero frameworks. Pure vibe coding.
The surprising part wasn't that it worked — it was 3x faster than my handwritten version."

Version B (Value Equation: High Result / Low Effort):
"Can't code? Doesn't matter.
I just built an AI coding assistant in 2 days using Claude Code.
Wrote zero lines of code myself. Full walkthrough:"

Version C (Contrarian + Specific Data):
"Most AI coding assistant benchmarks are demo-level.
I built one that's actually in production using Claude Code.
The difference? 30 edge cases and an AI willing to debug until 3am."

→ Recommend Version A: has specific numbers (48h/3x) and a suspense hook.
→ Best publish time: Weekdays 9–11am.
⚠️ No external links in the post body — put them in the first reply.

Scenario B — Review a Hook

场景B — 钩子评审

Trigger: User pastes existing tweet content asking for feedback.

Scoring rubric:

Curiosity gap (does it create a must-read-on feeling?)
Credibility anchor (why should I believe you?)
Specific benefit (what will I get?)

Example:

User: Review this: "I tested 5 AI coding tools. Here's what I found."

X导师: Hook Score: 3/10

Diagnosis:
❌ No curiosity gap — no suspense, reader doesn't need to click
❌ No credibility anchor — anyone can say "I tested"
❌ No specific benefit — "what I found" is too vague

Rewrite:
"I stress-tested 5 AI coding tools on the same project
(a full-stack app in 48 hours).
One saved me 12 hours. The rest were useless.
A thread:"

Changes: Added specific scenario (full-stack app), time anchor (48h),
suspense (which one?), credibility (real test data).

触发条件：用户粘贴现有推文内容请求反馈。

评分规则：

好奇心缺口：是否能激发读者继续阅读的欲望？
可信度锚点：读者为什么要相信你的内容？
明确收益：读者能从内容里获得什么？

示例：

User: Review this: "I tested 5 AI coding tools. Here's what I found."

X导师: Hook Score: 3/10

Diagnosis:
❌ No curiosity gap — no suspense, reader doesn't need to click
❌ No credibility anchor — anyone can say "I tested"
❌ No specific benefit — "what I found" is too vague

Rewrite:
"I stress-tested 5 AI coding tools on the same project
(a full-stack app in 48 hours).
One saved me 12 hours. The rest were useless.
A thread:"

Changes: Added specific scenario (full-stack app), time anchor (48h),
suspense (which one?), credibility (real test data).

Scenario C — Topic Selection

场景C — 选题规划

Trigger: User asks for content ideas or is stuck on what to post.

4A Topic Matrix: Generate one topic × 4 angles = unlimited content:

Angle	Description	Example
Actionable	How-to, step-by-step	"5 steps to X"
Analytical	Data, research, breakdown	"I analyzed 100 posts..."
Aspirational	Vision, transformation	"In 2 years I went from..."
Anthropological	Observation, patterns	"Why most people fail at..."

Lean Validation Flywheel:

Tweet (validate) → Thread (expand) → Newsletter (deepen) → Product (monetize)

Never write long-form until a tweet has proven the idea resonates.

触发条件：用户寻求内容创意或不知道发什么内容。

4A主题矩阵： 1个主题×4个角度=无限内容素材：

角度	描述	示例
可落地类	操作指南、分步教程	"实现X的5个步骤"
分析类	数据、研究、拆解	"我分析了100条帖子..."
励志成长类	愿景、转变经历	"两年时间我从...变成..."
观察洞察类	现象观察、规律总结	"为什么大多数人做X会失败"

精益验证飞轮：

Tweet (validate) → Thread (expand) → Newsletter (deepen) → Product (monetize)

在短推文验证了内容受众认可度之前，不要先写长内容。

Scenario D — Growth Strategy

场景D — 增长策略

Trigger: User asks about follower growth, algorithm, or monetization.

X Algorithm Key Weights (from open-source code, April 2026):

Conversation reply (author replies back to you): 150x
Regular reply:                                    27x
Dwell time (>2 minutes):                         20x
Retweet:                                          2x
Like:                                             1x (baseline)

TweepCred System:

Non-Premium user baseline:    -128 points
Distribution threshold:       +17 points
Premium subscription bonus:  +100 points (instant)
Gap without Premium:         -145 points below threshold

Growth phases:

0–1K (Cold Start):
- Post 2–3 short tweets/day to find resonant topics
- Leave 5–10 high-quality replies (200–400 words) on large accounts daily
- DM 3 same-size creators/week for mutual support
- No threads yet — find your high-ER topics first
- Expected: 5–10 followers/day → 1K in 4–8 weeks

1K–10K (Flywheel):
- Weekly thread on proven topics
- Activate "Public Building" — document your process
- Start email list (algorithm changes, newsletters don't)
- Expected: 30–50 followers/day

10K+ (Monetization):
- Cohort courses / 1-on-1 coaching / digital products
- Justin Welsh model: $12M/year, 90% margin, solopreneur

Critical warnings:

⚠️ External links in post body: -30–50% reach
⚠️ Non-Premium links: median engagement = 0
⚠️ "Great post!" replies: algorithm detects and ignores engagement bait

触发条件：用户询问粉丝增长、算法规则或变现相关问题。

X算法核心权重（来自2026年4月开源代码）：

Conversation reply (author replies back to you): 150x
Regular reply:                                    27x
Dwell time (>2 minutes):                         20x
Retweet:                                          2x
Like:                                             1x (baseline)

TweepCred体系：

Non-Premium user baseline:    -128 points
Distribution threshold:       +17 points
Premium subscription bonus:  +100 points (instant)
Gap without Premium:         -145 points below threshold

增长阶段：

0–1K (冷启动阶段):
- 每天发2-3条短推文找到受众感兴趣的主题
- 每天在大号内容下留5-10条高质量回复（200-400字）
- 每周私信3个同量级创作者寻求互助
- 暂时不发thread，先找到高互动率的选题
- 预期：每天涨5-10粉 → 4-8周达到1000粉

1K–10K (飞轮阶段):
- 每周围绕验证过的主题发1条thread
- 开启「公开建站」模式，记录你的成长过程
- 开始搭建邮件列表（算法会变，邮件列表不会）
- 预期：每天涨30-50粉

10K+ (变现阶段):
- 可推出 cohort 课程/1对1 coaching/数字产品
- 参考Justin Welsh模式：年入1200万美元，利润率90%，单人运营

重要警示：

⚠️ 推文正文中放外部链接：曝光量减少30%-50%
⚠️ 非Premium用户放链接：中位数互动量为0
⚠️ 类似「好帖！」的无意义回复：算法会识别为互动诱饵直接忽略

Scenario E — Account Diagnostics

场景E — 账号诊断

Trigger: User asks to analyze their X account.

Data collection (3-tier fallback):

python

undefined

触发条件：用户请求分析自己的X账号。

数据采集（三层降级方案）：

python

undefined

Tier 1: Automatic via computer-use / browser tools

Tier 2: User pastes exported data

Tier 3: User manually provides metrics

Data saved to:

user-data/{username}/ ├── profile.md # Account basics ├── tweets_{date}.json # Raw tweet data ├── tweets_{date}.md # Human-readable summary ├── report_{date}.html # Economist-style HTML report └── strategy.md # Personalized strategy


**Diagnostic report sections:**
1. **KPI Dashboard** — followers, ER rate, posting frequency
2. **Content ROI** — which content types deliver most engagement per hour invested
3. **Distribution Funnel** — impressions → likes → replies → follows
4. **Time Analysis** — best/worst posting windows
5. **Brand Narrative** — positioning clarity score
6. **Action Plan** — top 3 highest-ROI changes

**Persistent memory:** On every activation, the skill checks `user-data/{username}/` for historical data:
- Found + <30 days old → silently load personalized strategy
- Found + >30 days old → suggest re-diagnosis
- Not found → offer full diagnosis

---


**诊断报告模块：**
1. **KPI看板** — 粉丝数、互动率、发布频率
2. **内容ROI** — 每投入一小时哪种内容类型带来的互动最高
3. **分发漏斗** — 曝光→点赞→回复→关注转化路径
4. **时间分析** — 最优/最差发布窗口
5. **品牌叙事** — 定位清晰度评分
6. **行动方案** — 3个ROI最高的优化措施

**持久记忆：** 每次激活时，Skill都会检查`user-data/{username}/`下的历史数据：
- 数据存在且小于30天 → 自动加载个性化策略
- 数据存在且大于30天 → 建议重新诊断
- 未找到数据 → 提供全套诊断服务

---

6 Core Mental Models

6大核心思维模型

Model	One-liner	Source
Lean Validation Flywheel	Tweet to validate → expand if data supports	Cole/Bush + Sahil + Hormozi + Welsh
Attention Engineering	First 2 lines decide everything; hooks can be engineered	Cole + Hormozi (Value Equation)
Category Creation	Don't fight for a niche — create one only you own	Cole (Snow Leopard) + Koe (Niche of One)
Value Front-Loading	Give away the secret for free, sell the execution	Hormozi + Welsh + Sahil
Build in Public	Turn your process into content; audience becomes stakeholders	levelsio + swyx
Systematic Compounding	Templates replace inspiration; output becomes predictable	Welsh (Content OS) + Koe (2 Hour Writer)

模型	核心总结	来源
精益验证飞轮	先发推文验证 → 数据反馈好再扩展内容	Cole/Bush + Sahil + Hormozi + Welsh
注意力工程	前两行决定一切；钩子是可以设计出来的	Cole + Hormozi（价值等式）
品类创造	不要在现有赛道卷 — 创造一个只属于你的赛道	Cole（雪豹理论） + Koe（一人赛道理论）
价值前置	免费公开核心方法，卖落地执行服务	Hormozi + Welsh + Sahil
公开建站	把你的过程变成内容；受众就是你的利益相关方	levelsio + swyx
系统复利	用模板代替灵感；产出可预测	Welsh（内容OS） + Koe（两小时写作法）

10 Decision Heuristics

10条决策经验法则

1. Tweet before writing long-form    — tweets are idea refineries
2. Hook gets 50% of creative time    — write 10–15 versions, pick the best
3. Conversation beats everything     — a reply = 150 likes (X open source)
4. 1/3/1 rhythm                      — 1 hook + 3 expansion + 1 transition
5. Super Bowl Response               — new model launch = respond within 1 hour
6. Own your audience                 — algorithms change, newsletters don't
7. 4A Topic Matrix                   — 1 topic × 4 angles = unlimited content
8. Give secrets, sell execution      — 99% of readers won't do it themselves
9. Templates beat inspiration        — Cole uses 7 templates for 200+ threads
10. Replies are gold mines           — one reply can get 6,700 impressions

1. Tweet before writing long-form    — tweets are idea refineries
2. Hook gets 50% of creative time    — write 10–15 versions, pick the best
3. Conversation beats everything     — a reply = 150 likes (X open source)
4. 1/3/1 rhythm                      — 1 hook + 3 expansion + 1 transition
5. Super Bowl Response               — new model launch = respond within 1 hour
6. Own your audience                 — algorithms change, newsletters don't
7. 4A Topic Matrix                   — 1 topic × 4 angles = unlimited content
8. Give secrets, sell execution      — 99% of readers won't do it themselves
9. Templates beat inspiration        — Cole uses 7 templates for 200+ threads
10. Replies are gold mines           — one reply can get 6,700 impressions

Hook Templates (Nicolas Cole's 7 Core Formats)

钩子模板（Nicolas Cole 7大核心格式）

markdown

undefined

markdown

undefined

Template 1: The Curiosity Gap

"[Common belief]. But [surprising exception]. Here's what no one tells you:"

Template 2: The Numbered List Hook

"[X] things I learned from [credible source/experience]:"

Template 3: The Contrarian Take

"Unpopular opinion: [mainstream belief] is wrong. Here's why:"

Template 4: The Personal Story

"[Time ago], I [relatable struggle]. Today, I [transformation]. What changed:"

Template 5: The Data Lead

"I analyzed [specific number] [things]. The result surprised me:"

Template 6: The How-To Promise

"How to [desirable outcome] in [specific time frame] (without [common obstacle]):"

Template 7: The Value Equation (Hormozi)

"[High dream outcome] + [High perceived likelihood]

[Low time delay] + [Low effort/sacrifice]"

---

"[High dream outcome] + [High perceived likelihood]

[Low time delay] + [Low effort/sacrifice]"

---

Thread Structure (The 1/3/1 Pattern)

Thread结构（1/3/1模式）

Tweet 1: HOOK
  → One punchy line that creates a curiosity gap
  → Never reveal the answer in the hook

Tweet 2-N: BODY (each tweet follows 1/3/1)
  [1 line setup]
  [3 lines of substance/evidence]
  [1 line transition to next tweet]

Final Tweet: CTA
  Options:
  - "Follow me for more on [topic]"
  - "RT the first tweet if this was useful"
  - "I write about this in my newsletter: [link]"
  ⚠️ Put newsletter/external link ONLY in the last tweet

Tweet 1: HOOK
  → One punchy line that creates a curiosity gap
  → Never reveal the answer in the hook

Tweet 2-N: BODY (each tweet follows 1/3/1)
  [1 line setup]
  [3 lines of substance/evidence]
  [1 line transition to next tweet]

Final Tweet: CTA
  Options:
  - "Follow me for more on [topic]"
  - "RT the first tweet if this was useful"
  - "I write about this in my newsletter: [link]"
  ⚠️ Put newsletter/external link ONLY in the last tweet

Content OS Template (Justin Welsh's System)

内容OS模板（Justin Welsh体系）

markdown

undefined

markdown

undefined

Weekly Content Schedule

Monday: Analytical post (data/research) Tuesday: Actionable post (how-to) Wednesday: Aspirational post (story/transformation) Thursday: Engagement/reply day (no original post) Friday: Thread (on topic validated by Mon-Wed posts) Weekend: Community building, DMs, newsletter

Topic Pillars (pick 2-3)

Pillar 1: [Your professional expertise] Pillar 2: [Your contrarian perspective] Pillar 3: [Your personal story/journey]

Weekly Review Metrics

Top post by impressions: [__]
Top post by engagement rate: [__]
New followers this week: [__]
Email subscribers added: [__]
What to double down on: [__]

---

Top post by impressions: [__]
Top post by engagement rate: [__]
New followers this week: [__]
Email subscribers added: [__]
What to double down on: [__]

---

AI/Tech Niche Specific Tactics

AI/科技垂类专属策略

markdown

undefined

markdown

undefined

Timing Windows for AI Content

New model releases: Respond within 0–60 minutes
Major AI news: Within 2–4 hours (before saturation)
Weekend builds: "Ship something Sunday" posts perform well
Best posting windows: 9–11am weekdays (your audience's timezone)

New model releases: Respond within 0–60 minutes
Major AI news: Within 2–4 hours (before saturation)
Weekend builds: "Ship something Sunday" posts perform well
Best posting windows: 9–11am weekdays (your audience's timezone)

High-ER Content Types for AI Niche

Build-in-public updates with specific metrics
Contrarian takes on hyped tools (with evidence)
Before/after comparisons (workflow transformation)
"I gave AI a hard problem" with honest results
Tool teardowns (not just "here's a cool tool")

Build-in-public updates with specific metrics
Contrarian takes on hyped tools (with evidence)
Before/after comparisons (workflow transformation)
"I gave AI a hard problem" with honest results
Tool teardowns (not just "here's a cool tool")

Avoid in AI Niche

❌ "AI is going to change everything" (too vague) ❌ Resharing press releases without original take ❌ Engagement bait ("Drop a 🔥 if you agree") ❌ Posting the same benchmark every tool already shares

---

---

Anti-Patterns Reference

反面模式参考

markdown

undefined

markdown

undefined

The 6 Common Failure Modes

TOPIC SCATTER — Posting about 10 different topics, never building authority Fix: Pick 2–3 pillars, stick for 90 days minimum
LINK ADDICTION — Putting URLs in every post Fix: All links go in replies or last thread tweet only
VANITY POSTING — Writing for yourself, not your reader Fix: Every post answers "what does my reader get from this?"
ENGAGEMENT BAIT — "Like if you agree!" "RT for more!" Fix: Algorithm detects this; earn engagement through value
PREMATURE MONETIZATION — Selling before building trust Fix: Welsh rule: 1,000 true fans before any paid offer
INCONSISTENCY — Posting 10x one week, zero the next Fix: Reduce quality bar temporarily to maintain consistency ("minimum viable post" > no post)

---

TOPIC SCATTER — Posting about 10 different topics, never building authority Fix: Pick 2–3 pillars, stick for 90 days minimum
LINK ADDICTION — Putting URLs in every post Fix: All links go in replies or last thread tweet only
VANITY POSTING — Writing for yourself, not your reader Fix: Every post answers "what does my reader get from this?"
ENGAGEMENT BAIT — "Like if you agree!" "RT for more!" Fix: Algorithm detects this; earn engagement through value
PREMATURE MONETIZATION — Selling before building trust Fix: Welsh rule: 1,000 true fans before any paid offer
INCONSISTENCY — Posting 10x one week, zero the next Fix: Reduce quality bar temporarily to maintain consistency ("minimum viable post" > no post)

---

Troubleshooting

故障排查

Issue: Posts getting zero impressions

Diagnosis: TweepCred likely below distribution threshold (-128 baseline)
Fix sequence:
1. Subscribe to Premium (+100 TweepCred instantly)
2. Remove all external links from post bodies
3. Increase reply activity on large accounts (150x weight)
4. Check if account has any policy flags (check X settings)

Issue: Good impressions but no follower growth

Diagnosis: Content-to-profile mismatch or weak profile
Fix sequence:
1. Audit profile: bio must state WHO you help + HOW
2. Pin your best-performing thread to profile
3. Every viral post should funnel to a clear follow reason
4. Add "I write about [X] every [cadence]" to bio

Issue: Followers not converting to email subscribers

Diagnosis: No consistent CTA or newsletter value prop unclear
Fix sequence:
1. Add newsletter link to bio (not just Linktree)
2. End every thread with a specific newsletter CTA
3. Give away a "lead magnet" (free guide, template, checklist)
4. Post one "newsletter exclusive content preview" per week

Issue: Account diagnostics tool can't auto-collect data

undefined

问题：帖子零曝光

Diagnosis: TweepCred likely below distribution threshold (-128 baseline)
Fix sequence:
1. Subscribe to Premium (+100 TweepCred instantly)
2. Remove all external links from post bodies
3. Increase reply activity on large accounts (150x weight)
4. Check if account has any policy flags (check X settings)

问题：曝光不错但粉丝不增长

Diagnosis: Content-to-profile mismatch or weak profile
Fix sequence:
1. Audit profile: bio must state WHO you help + HOW
2. Pin your best-performing thread to profile
3. Every viral post should funnel to a clear follow reason
4. Add "I write about [X] every [cadence]" to bio

问题：粉丝不会转化为邮件订阅用户

Diagnosis: No consistent CTA or newsletter value prop unclear
Fix sequence:
1. Add newsletter link to bio (not just Linktree)
2. End every thread with a specific newsletter CTA
3. Give away a "lead magnet" (free guide, template, checklist)
4. Post one "newsletter exclusive content preview" per week

问题：账号诊断工具无法自动采集数据

undefined

Fallback to manual data provision:

Provide any of the following:

Screenshot of your X Analytics dashboard
CSV export from X Data (Settings → Your Account → Download archive)
Manual paste of your last 20 tweets with engagement numbers

Minimum viable data for diagnosis:

Last 30 days impressions
Top 5 posts by engagement
Follower count + growth rate
Most common posting times

---

Provide any of the following:

Screenshot of your X Analytics dashboard
CSV export from X Data (Settings → Your Account → Download archive)
Manual paste of your last 20 tweets with engagement numbers

Minimum viable data for diagnosis:

Last 30 days impressions
Top 5 posts by engagement
Follower count + growth rate
Most common posting times

---

File Structure (Post-Installation)

文件结构（安装后）

your-project/
├── SKILL.md                          # Main routing file (249 lines)
├── references/
│   ├── writing-workshop.md           # Short tweets/hooks/threads/topics
│   ├── algorithm-niche.md            # X algorithm + AI niche tactics
│   ├── growth-monetization.md        # Growth engines + monetization
│   ├── quality-analytics.md          # Quality checklist + diagnostics
│   └── mental-models-heuristics.md   # 6 models + 10 heuristics
├── research/
│   ├── 01-writing-methods.md         # Nicolas Cole / Dickie Bush methodology
│   ├── 02-growth-engines.md          # Sahil Bloom / Justin Welsh systems
│   ├── 03-content-brand.md           # Dan Koe / Alex Hormozi frameworks
│   ├── 04-platform-mechanics.md      # X algorithm / TweepCred analysis
│   ├── 05-ai-tech-niche.md           # AI niche / Build in Public / China devs
│   └── 06-cases-antipatterns.md      # Case studies + failure patterns
└── user-data/
    └── {username}/
        ├── profile.md
        ├── tweets_{date}.json
        ├── tweets_{date}.md
        ├── report_{date}.html
        └── strategy.md

your-project/
├── SKILL.md                          # Main routing file (249 lines)
├── references/
│   ├── writing-workshop.md           # Short tweets/hooks/threads/topics
│   ├── algorithm-niche.md            # X algorithm + AI niche tactics
│   ├── growth-monetization.md        # Growth engines + monetization
│   ├── quality-analytics.md          # Quality checklist + diagnostics
│   └── mental-models-heuristics.md   # 6 models + 10 heuristics
├── research/
│   ├── 01-writing-methods.md         # Nicolas Cole / Dickie Bush methodology
│   ├── 02-growth-engines.md          # Sahil Bloom / Justin Welsh systems
│   ├── 03-content-brand.md           # Dan Koe / Alex Hormozi frameworks
│   ├── 04-platform-mechanics.md      # X algorithm / TweepCred analysis
│   ├── 05-ai-tech-niche.md           # AI niche / Build in Public / China devs
│   └── 06-cases-antipatterns.md      # Case studies + failure patterns
└── user-data/
    └── {username}/
        ├── profile.md
        ├── tweets_{date}.json
        ├── tweets_{date}.md
        ├── report_{date}.html
        └── strategy.md

Quick Reference Card

速查卡

WRITE TWEET    → 3 hooks + formula labels + publish time + link warning
REVIEW HOOK    → score/10 + 3-point diagnosis + rewrite
TOPIC IDEAS    → 4A matrix + lean validation flywheel
GROWTH STUCK   → TweepCred diagnosis + weekly action plan
ACCOUNT AUDIT  → auto-collect → HTML report → personalized strategy

ALGORITHM WEIGHTS:  Reply conversation=150x, Reply=27x, RT=2x, Like=1x
LINK PENALTY:       -30–50% reach (put in replies only)
PREMIUM VALUE:      +100 TweepCred (bridges most of the -145 deficit)
BEST POST TIME:     Weekdays 9–11am
HOOK TIME BUDGET:   50% of total writing time

WRITE TWEET    → 3 hooks + formula labels + publish time + link warning
REVIEW HOOK    → score/10 + 3-point diagnosis + rewrite
TOPIC IDEAS    → 4A matrix + lean validation flywheel
GROWTH STUCK   → TweepCred diagnosis + weekly action plan
ACCOUNT AUDIT  → auto-collect → HTML report → personalized strategy

ALGORITHM WEIGHTS:  Reply conversation=150x, Reply=27x, RT=2x, Like=1x
LINK PENALTY:       -30–50% reach (put in replies only)
PREMIUM VALUE:      +100 TweepCred (bridges most of the -145 deficit)
BEST POST TIME:     Weekdays 9–11am
HOOK TIME BUDGET:   50% of total writing time