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panini-extractor

Extracts player data and images from Panini sticker album PDFs into TypeScript squad files.

Updated May 14, 2026
Search Tags:#typescript#data extraction#pdf#vision#football#image conversion#panini
One-click install
npx skills add https://github.com/jesusprodriguezUnir/bracketMundial --skill panini-extractor-jesusprodriguezunir
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: panini-extractor
Source: https://github.com/jesusprodriguezUnir/bracketMundial/tree/main/.agents/skills/panini-extractor
Command: npx skills add https://github.com/jesusprodriguezUnir/bracketMundial --skill panini-extractor-jesusprodriguezunir

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PyPDF2, pdf2image, Pillow.

What problem does it solve? Manually transcribing player rosters from scanned Panini sticker album PDFs into a project's squad database is slow and error-prone. This Skill uses the agent's vision capabilities to read the PDF pages directly and write structured player data into TypeScript files. ## Core Features & Use Cases - Vision-Based PDF Reading: Renders Panini album PDFs as images and extracts each player's name, birth date, club, and position from the stickers. - Squad Database Updates: Maps extracted players to the correct national team file under src/data/squads/ and updates the squad array and lineup while respecting the existing TypeScript Player model. - Image Extraction & Optimization: Pulls sticker images from the PDF, converts them to .webp at 512x512 pixels, and organizes them by team under public/assets/players/. - Use Case: Given docs/HOLANDA.pdf, extract all Netherlands players, compute ages relative to 2026, update src/data/squads/ned.ts, and save player images to public/assets/players/NED/. ## Quick Start Extract the player data from docs/HOLANDA.pdf and update the corresponding squad file in src/data/squads/.

Frequently Asked Questions about panini-extractor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract player data from a Panini album PDF?▼

Point the agent at the PDF file, and it renders the pages as images using its vision capability. It then reads each sticker to extract the player's name, birth date, club, and position, and writes the results into the team's TypeScript squad file.

How are player ages and positions determined from stickers?▼

Age is computed by subtracting the birth year printed on the sticker from the tournament year 2026. Position (GK, DF, MF, FW) is inferred from the icon in the sticker's top-right corner combined with general football knowledge.

Can I extract sticker images from the PDF as webp files?▼

Yes. The Skill extracts images from the PDF pages, converts them to .webp format, resizes them to 512x512 pixels, and organizes them by team under public/assets/players/, for example public/assets/players/ARG/messi.webp.

What happens if a sticker does not show the shirt number?▼

Panini stickers typically lack exact shirt numbers. The Skill infers the number from general knowledge of the player or keeps the number already defined in the existing team file, and updates the lineup variable if numbers change.

What are the limitations of vision-based PDF extraction?▼

Accuracy depends on the scan quality of the album pages; blurry or low-resolution stickers can cause misread names or dates. Extracted data should be reviewed against the source before committing changes to the squad files.

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