What problem does it solve?
Writing WeChat official account titles that achieve high open rates is guesswork for most authors. This Skill removes the guesswork by reusing a reference library of real titles with verified open-rate, recommendation, and share data, filling their slots with your article's actual keywords instead of inventing untested phrasing.
Core Features & Use Cases
- Template-Based Generation: Extracts keywords (companies, products, numbers, events, emotions) from your article and fills them into proven title templates from references/title-data.md, changing only proper nouns and numbers.
- Data-Driven Selection: Ranks candidate templates by real open rate, recommendation rate, and share count, skipping templates that do not match the article's content type.
- Verifiable Output: Produces five candidate titles in a side-by-side comparison format showing the original template, the substitutions made, and character-count differences, plus a short title suggestion.
- Use Case: After finishing an article about a newly open-sourced AI tool, provide the file path and receive five titles modeled on templates that historically achieved 4-6% open rates.
Quick Start
Ask the assistant to generate five high-open-rate titles for your finished article by providing its file path or a summary of its topic and keywords.
