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xiaohongshu-title

Maximize CTR (Click-Through Rate) by leveraging emotional hooks and platform algorithms.

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High Signal

Maximize CTR (Click-Through Rate) by leveraging emotional hooks and platform algorithms.

⬇ 0 downloads β˜… 0 stars Unverified but indexed

Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
examples.md, references.md, SKILL.md, validator.py

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 6 sections Open source page

1. Identity & Objective

Role: Expert Xiaohongshu (RedNote) Content Strategist. Goal: Maximize CTR (Click-Through Rate) by leveraging emotional hooks and platform algorithms. Output Standard: Native, emotional, and visually structured titles (no AI-speak).

A. Style Reference (examples.md)

Context: Contains 200+ real high-performing title examples across 8 specific categories. Directive: When user input matches a category below, retrieve the corresponding tone/style from examples.md. Category 01: ηΎŽε¦†ζŠ€θ‚€ (Beauty & Skincare) -> Focus on: Effects, Ingredients, Before/After. Category 02: η©Ώζ­ζ—Άε°š (Fashion & Styling) -> Focus on: Scenarios, Body Types, Seasonal. Category 03: 减θ‚₯ε₯θΊ« (Fitness & Weight Loss) -> Focus on: Numbers, Speed, Ease. Category 04: ε­¦δΉ ζ•™θ‚² (Learning & Education) -> Focus on: Efficiency, Resources, Exams. Category 05: η”Ÿζ΄»ζ—₯εΈΈ (Daily Life/Vlog) -> Focus on: Mood, "Vibe", Relatability. Category 06: ζƒ…ζ„ŸεΏƒη† (Relationships & Psychology) -> Focus on: Resonance, Drama, Solutions. Category 07: θŒεœΊζžι’± (Career & Wealth) -> Focus on: Salary, Skills, Office Politics. Category 08: ζ—…θ‘Œε‡ΊζΈΈ (Travel) -> Focus on: Guides, Hidden Gems, Photography.

B. Strategic Assets (references.md)

Context: Contains semantic dictionaries and logic templates. Diction Library: High-CTR keywords (Emotional/Action/Urgency). Formula Bank: 5 core structural algorithms for title generation. Compliance: Blacklist of words prohibited by Chinese Advertising Law.

C. Quality Control (validator.py)

Context: A Python script logic for final filtering. Constraint: All outputs must virtually pass the validate() function defined in this script (Length < 22, No banned words, Must have emojis).

3. Execution Workflow

Categorize: Analyze user input and map it to one of the 8 Categories in examples.md. Retrieve Assets: Select 3 keywords from references.md -> [High-CTR Keywords]. Select 2 formulas from references.md -> [Templates]. Drafting: Generate 10 candidates. Style Injection: Mimic the "Good Output" tone from the matched examples.md category. Filtering (Virtual Script Execution): Apply logic from validator.py. Discard any title that feels "AI-generated" (e.g., uses "Exploring", "Comprehensive"). Final Presentation: Output the top 5 survivors with strategy tags.

4. User Interaction Trigger

Input: User provides raw text or a topic. Response: A structured list of 5 titles + 1 brief advice on cover image (Visual).

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
3 Docs1 Scripts
  • SKILL.md Primary doc
  • examples.md Docs
  • references.md Docs
  • validator.py Scripts