Nex Datasheet Extractor

    by Nex AI

    1

    Extracts structured electrical specs, package data, and compliance status from component datasheet PDFs.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurfMManus+14 more

    See it in action

    You say

    Extract the specs from components/stm32f4.pdf and save it as a CSV row for my library.

    Your agent does

    Extraction complete. Created stm32f4.csv: part_number: STM32F405RG manufacturer: STMicroelectronics package: LQFP64 supply_voltage_min: 1.8 supply_voltage_max: 3.6 operating_temp_min: -40 operating_temp_max: 85 rohs_status: Compliant confidence: high

    What you get

    Convert PDF datasheets into structured JSON or CSV rows.Identify electrical constraints like voltage and temperature ranges.Extract package and pin count data for footprint assignment.Automate RoHS and REACH compliance verification for components.

    About this skill

    The problem

    Manually transcribing electrical specifications from PDF datasheets into component libraries is slow and prone to human error. Developers and hardware engineers often waste hours hunting for supply voltages, temperature ranges, and package types across multi-page documents.

    What it does

    • Parses PDF text layers to extract primary part numbers and manufacturer names.
    • Identifies key electrical parameters including min/max supply voltages and operating temperatures.
    • Extracts mechanical data like package strings and pin counts for footprint mapping.
    • Checks for RoHS and REACH compliance status within the document text.
    • Outputs structured data in JSON or CSV format for direct library ingestion.

    Frameworks & tools

    Python, pdfminer.six, pytest.

    Why this beats prompting it yourself

    General LLM prompting for PDF extraction often suffers from hallucination of numerical values or inconsistent formatting. This skill uses a specialized script to target specific datasheet patterns, providing a structured output with an extraction confidence score to flag entries needing manual review.

    Use cases

    • Populating an ECAD component library (Altium, KiCad) from a batch of PDFs.
    • Automating compliance checks for large BOMs by extracting RoHS/REACH status.
    • Building a searchable internal database of component electrical characteristics.

    Known limitations

    Only works on PDFs with a text layer. Scanned images or tables formatted as images will not be captured. Requires manual verification of electrical parameters before library commitment.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Creator

    Nex AI
    Nex AI

    249 skills on Agensi

    Founder of Nex AI. I build production-grade Claude Skills from systems that actually run: multi-tenant SaaS, Telegram agents, Raspberry Pi infrastructure, 3D multiplayer rooms. Every skill ships battle-tested patterns, not theory. 33+ open source skills published, commercial catalog growing.

    Frequently Asked Questions

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