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Found 104 Skills
Customer.io platform help — customer engagement & marketing automation for behavior-based multi-channel messaging. Journeys (visual workflow builder with branching, delays, wait-untils), Campaigns (segment/event/date-triggered), Transactional Messages (API-triggered email, push, SMS), Segmentation (data-driven auto-updating and manual/static), Multi-channel (email, SMS via Twilio, push iOS/Android/web, in-app, WhatsApp), Data Pipelines (primary ingestion API, reverse ETL), Custom Objects, Ad Audience Sync (Google, Facebook, Instagram, YouTube), Design Studio (drag-and-drop email editor), A/B & cohort testing, Broadcasts (one-time/scheduled/API-triggered), Webhooks in workflows, and Analytics with AI-powered insights. Use when asking 'how do I do X in Customer.io', building behavior-triggered automation, setting up transactional messaging via Customer.io, configuring segments or journeys, integrating Customer.io Data Pipelines, or working with the Track/App/Transactional APIs. Do NOT use for general email marketing strategy (use /sales-email-marketing), cross-platform email deliverability (use /sales-deliverability), or email open/click tracking strategy (use /sales-email-tracking).
Visual ChangeNet for binary image classification and segmentation in AOI defect detection. Use when training, evaluating, exporting, or running inference for PCB defect detection or visual inspection, comparing image pairs for PASS/NO_PASS classification, or producing change-segmentation masks. Trigger phrases include "train Visual ChangeNet", "ChangeNet classify", "ChangeNet segment", "AOI defect detection", "PCB inspection model".
OneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a TAO OneFormer model. Trigger phrases include "train OneFormer", "universal segmentation", "task-conditioned segmentation", "panoptic / instance / semantic in one model".
Use when implementing ANY computer vision feature - image analysis, object detection, pose detection, person segmentation, subject lifting, hand/body pose tracking.
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
Configure host-based firewalls (iptables, nftables, UFW) and cloud security groups (AWS, GCP, Azure) with practical rules for common scenarios like web servers, databases, and bastion hosts. Use when exposing services, hardening servers, or implementing network segmentation with defense-in-depth strategies.
Multimodal AI processing via Google Gemini API (2M tokens context). Capabilities: audio (transcription, 9.5hr max, summarization, music analysis), images (captioning, OCR, object detection, segmentation, visual Q&A), video (scene detection, 6hr max, YouTube URLs, temporal analysis), documents (PDF extraction, tables, forms, charts), image generation (text-to-image, editing). Actions: transcribe, analyze, extract, caption, detect, segment, generate from media. Keywords: Gemini API, audio transcription, image captioning, OCR, object detection, video analysis, PDF extraction, text-to-image, multimodal, speech recognition, visual Q&A, scene detection, YouTube transcription, table extraction, form processing, image generation, Imagen. Use when: transcribing audio/video, analyzing images/screenshots, extracting data from PDFs, processing YouTube videos, generating images from text, implementing multimodal AI features.
Segment users from feedback data based on behavior, JTBD, and needs. Identifies at least 3 distinct user segments. Use when segmenting a user base, analyzing diverse user feedback, or building a segmentation model.
Data-driven customer persona development combining market research, user behavior analysis, and segmentation frameworks. Use when creating buyer personas, ideal customer profiles (ICPs), or user archetypes.
Solidify the workflow skill of "literature retrieval and scheduled push". It is used to create cron tasks for automatic retrieval + structured summary + multi-channel push (Feishu/WeCom/QQ/Telegram) for topics such as MDRGNB/HCC on a daily/weekly/monthly basis; supports field standardization (journal name, CAS Partition, SCI Partition), consistent content across multiple terminals, and long text segmentation to prevent loss. Trigger examples: "Help me push xx literature to xx at xx:xx", "Push xx topic literature to xx channel at xx:xx daily/weekly/monthly"
Use this skill when designing email campaigns, building drip sequences, improving deliverability, or A/B testing email content. Triggers on email campaigns, drip sequences, newsletter, email deliverability, subject lines, email automation, segmentation, open rates, click-through rates, and any task requiring email marketing strategy or execution.
Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.