Nexus Reader Daily WeRead Rising List Recommendations
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About this skill
Problem
Manual daily selection from WeRead's rising list, recommendation copy, and card layout is repetitive and hard to keep visually consistent. nexus-reader separates data fetching, LLM-assisted copywriting, and card rendering into a reusable workflow.
How it works
- Fetch the top 20 WeRead rising-list books and save them to
data/weread_rising_YYYY-MM-DD.json, including title, author, and recommendation score. - Use an LLM to create
book_desc, a headline, recommendation copy, andlunar_date, then writedata/nexus-reader-YYYYMMDD.json. - Render an HTML card from the card JSON and optionally export a PNG. Cover, rating, and reading count fields are taken from the fetched data to avoid inventing metadata.
Boundaries
This skill is best for consistent daily reading cards, not in-depth book reviews or cross-platform publishing. Cover images depend on a CDN and may fail in weak network conditions; PNG export requires an optional dependency. Same-day cache can be reused, and the workflow falls back to older cache if fetching fails.
Use Cases
- A reading-account operator fetches 20 WeRead rising-list books daily and renders a consistent HTML daily card.
- A content editor converts the WeRead rising list into a shareable image by rendering HTML and exporting a PNG card.
- An automation engineer schedules a daily 08:00 job to fetch data, generate card JSON, and push an HTML preview link.
- A personal reading-stream maintainer keeps real title, rating, and reading count fields while asking an LLM to add copy and lunar date.
Best For
- content operators maintaining daily reading cards with a fixed visual template and list data source
- content editors turning WeRead rankings into social sharing images
- LLM workflow engineers building daily scheduled reading-recommendation automation
- reading-assistant maintainers who need real ratings and reader counts while using models only for copy
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