title

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

Security Scan

The skill's files, instructions, and requirements are consistent with its stated purpose (generating high‑CTR Xiaohongshu titles); it doesn't request credentials, installs, or hidden endpoints.

Purpose & Capability

Name/description (maximize CTR for Xiaohongshu) align with the provided assets: examples.md (style examples), references.md (keywords/templates/blacklist), and validator.py (final filtering rules). No unrelated env vars, binaries, or config paths are requested.

Instruction Scope

SKILL.md instructs the agent to categorize input, pull examples/templates/keywords from included files, draft candidates, and apply the local validator.py filter. It does not instruct reading unrelated system files, contacting external endpoints, or exfiltrating data. The only file access is to the bundled reference files and validator.

Install Mechanism

This is an instruction-only skill (no install spec). The only code is a small local Python validator script; there are no downloads, third‑party package installs, or archive extraction. Risk from install mechanism is low.

Credentials

The skill requires no environment variables, credentials, or config paths. All required inputs are user-provided text and bundled reference files; requested access is proportionate to the purpose.

Persistence & Privilege

always is false and there is no request for persistent or cross-skill configuration. The skill does not ask to modify other skills or system-wide settings.

Assessment

This skill is internally coherent and appears to do what it claims: generate attention-grabbing Xiaohongshu titles using the included examples, keyword dictionary, templates, and a local Python validator. Before installing, consider: (1) provenance — the owner and homepage are unknown, so treat it as unverified third‑party content; (2) runtime — the agent may execute the bundled validator.py locally, so ensure your agent environment permits executing small Python scripts and that you are comfortable running code from this unverified source; (3) compliance/ethics — the skill intentionally optimizes for emotional hooks and urgency (clickbait); review outputs for legal compliance, platform rules, and ethical concerns (misinformation, sensationalism, prohibited ad claims); (4) test outputs on non-sensitive topics first to confirm behavior. No network calls or secret exfiltration are apparent from the files provided.

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).

2. Knowledge Graph (File Mapping)

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: 美妆护肤 (Beauty & Skincare) -> Focus on: Effects, Ingredients, Before/After.
• Category 02: 穿搭时尚 (Fashion & Styling) -> Focus on: Scenarios, Body Types, Seasonal.
• Category 03: 减肥健身 (Fitness & Weight Loss) -> Focus on: Numbers, Speed, Ease.
• Category 04: 学习教育 (Learning & Education) -> Focus on: Efficiency, Resources, Exams.
• Category 05: 生活日常 (Daily Life/Vlog) -> Focus on: Mood, "Vibe", Relatability.
• Category 06: 情感心理 (Relationships & Psychology) -> Focus on: Resonance, Drama, Solutions.
• Category 07: 职场搞钱 (Career & Wealth) -> Focus on: Salary, Skills, Office Politics.
• Category 08: 旅行出游 (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

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