MCPInstall

x-mentor-skill-nuwa

AI-powered X (Twitter) content strategy skill that distills methodologies from 6 top creators + open-source algorithm data into actionable writing, growth, and monetization guidance.

Installs
595
Last 24h
—
Trending rank
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Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/reason-machines/trending-skills --skill x-mentor-skill-nuwa
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads x-mentor-skill-nuwa automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

X导师.skill (X Mentor 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.


Installation

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"

Five Core Scenarios

Scenario A — Write a Tweet

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

Workflow:

  1. Clarify format (short tweet vs. thread) and target audience
  2. Generate 3 hook variants with formula labels
  3. Recommend best version with rationale
  4. 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.

Scenario B — Review a Hook

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).

Scenario C — Topic Selection

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

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

AngleDescriptionExample
ActionableHow-to, step-by-step"5 steps to X"
AnalyticalData, research, breakdown"I analyzed 100 posts..."
AspirationalVision, transformation"In 2 years I went from..."
AnthropologicalObservation, 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.


Scenario D — Growth Strategy

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

Scenario E — Account Diagnostics

Trigger: User asks to analyze their X account.

Data collection (3-tier fallback):

# 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

6 Core Mental Models

ModelOne-linerSource
Lean Validation FlywheelTweet to validate → expand if data supportsCole/Bush + Sahil + Hormozi + Welsh
Attention EngineeringFirst 2 lines decide everything; hooks can be engineeredCole + Hormozi (Value Equation)
Category CreationDon't fight for a niche — create one only you ownCole (Snow Leopard) + Koe (Niche of One)
Value Front-LoadingGive away the secret for free, sell the executionHormozi + Welsh + Sahil
Build in PublicTurn your process into content; audience becomes stakeholderslevelsio + swyx
Systematic CompoundingTemplates replace inspiration; output becomes predictableWelsh (Content OS) + Koe (2 Hour Writer)

10 Decision Heuristics

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)

## 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]"

Thread Structure (The 1/3/1 Pattern)

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)

## 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: [__]

AI/Tech Niche Specific Tactics

## 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)

## High-ER Content Types for AI Niche
1. Build-in-public updates with specific metrics
2. Contrarian takes on hyped tools (with evidence)
3. Before/after comparisons (workflow transformation)
4. "I gave AI a hard problem" with honest results
5. 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

## The 6 Common Failure Modes

1. TOPIC SCATTER — Posting about 10 different topics, never building authority
   Fix: Pick 2–3 pillars, stick for 90 days minimum

2. LINK ADDICTION — Putting URLs in every post
   Fix: All links go in replies or last thread tweet only

3. VANITY POSTING — Writing for yourself, not your reader
   Fix: Every post answers "what does my reader get from this?"

4. ENGAGEMENT BAIT — "Like if you agree!" "RT for more!"
   Fix: Algorithm detects this; earn engagement through value

5. PREMATURE MONETIZATION — Selling before building trust
   Fix: Welsh rule: 1,000 true fans before any paid offer

6. INCONSISTENCY — Posting 10x one week, zero the next
   Fix: Reduce quality bar temporarily to maintain consistency
      ("minimum viable post" > no post)

Troubleshooting

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

# 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

File Structure (Post-Installation)

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

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

FAQ

What does the x-mentor-skill-nuwa skill do?

AI-powered X (Twitter) content strategy skill that distills methodologies from 6 top creators + open-source algorithm data into actionable writing, growth, and monetization guidance.

How do I install x-mentor-skill-nuwa?

Run npx skills add https://github.com/reason-machines/trending-skills --skill x-mentor-skill-nuwa in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/x-mentor-skill-nuwa/ (personal) or .claude/skills/x-mentor-skill-nuwa/ (project).

Which AI agents can use x-mentor-skill-nuwa?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is x-mentor-skill-nuwa safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains x-mentor-skill-nuwa?

It is published by reason-machines in reason-machines/trending-skills. It has 595 recorded installs.

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