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Found 131 Skills
Universal Cross-session Memory Protocol (Universal Memory Protocol). Enable all AI programming tools to share the same memory system. Applicable to Claude Code / Cursor / Aider / Cline / Codex / Trae / OpenCode. Capabilities: Intelligent Classification / FSRS Decay / Monthly Compression / Multi-layer Retrieval. Triggers: User says "remember"; asks "previous"; sensitive information detected; session ends.
Extract full paper details from a CNKI paper page including title, authors, affiliations, abstract, keywords, fund, classification. Use when the user needs detailed information about a specific paper.
Use this skill when building computer vision applications, implementing image classification, object detection, or segmentation pipelines. Triggers on image classification, object detection, YOLO, semantic segmentation, image preprocessing, data augmentation, transfer learning, CNN architectures, vision transformers, and any task requiring visual recognition or image analysis.
Use this skill when managing production incidents, designing on-call rotations, writing runbooks, conducting post-mortems, setting up status pages, or running war rooms. Triggers on incident response, incident commander, on-call schedule, pager escalation, runbook authoring, post-incident review, blameless retro, status page updates, war room coordination, severity classification, and any task requiring structured incident lifecycle management.
Reddit community moderation via PRAW with LLM-powered report classification: fetch modqueue, classify reports against subreddit rules and author history, and take mod actions (approve, remove, lock). Supports interactive, auto, and dry-run modes.
Build Next.js web applications with Google Gemini Nano Banana image generation APIs (gemini-2.5-flash-image, gemini-3-pro-image-preview). Use when creating image generators, editors, galleries, or any app integrating conversational image generation with server actions, API routes, and storage. Use for "image generation app", "nano banana", "text to image", "AI image generator", or "gemini image". Do NOT use for non-Gemini models, Python/Go backends, model fine-tuning, or image classification/input tasks.
4-phase code review methodology: UNDERSTAND changes, VERIFY claims against code, ASSESS security/performance/architecture risks, DOCUMENT findings with severity classification. Use when reviewing pull requests, auditing code before release, evaluating external contributions, or pre-merge verification. Use for "review PR", "code review", "audit code", "check this PR", or "review my changes". Do NOT use for writing new code or implementing features.
Performance and load testing patterns — k6 load tests, Locust stress tests, pytest execution optimization (xdist parallel, plugins), test type classification, and performance benchmarking. Use when writing load tests, optimizing test execution speed, or setting up pytest infrastructure.
A library of creative mechanics — the structural patterns that define how an ad constructs meaning between its hook, visuals, and narrative. Use this whenever designing ad concepts, briefing creative, or trying to explain why a specific ad works beyond just its hook or format. Trigger when a user describes an ad they saw and wants to understand or replicate what made it work, when building a creative concept from a messaging angle, or when execution needs more than a hook and a format — it needs a structural idea. Creative mechanics sit between hooks and visual formats in the Creative Strategy Engine: hooks say what, formats show how, mechanics define the cognitive or emotional mechanism that makes the concept land. Always pair with Hook Writing for opening line execution and Hook Tactics for tactic classification.
Apply when designing or modifying a BFF (Backend-for-Frontend) layer, middleware, or API proxy for a headless VTEX storefront. Covers BFF middleware architecture, public vs private API classification, VtexIdclientAutCookie management, API key protection, and secure request proxying. Use for any headless commerce project that must never expose VTEX_APP_KEY or call private VTEX APIs from the browser.
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics. Use this skill when the user needs to optimize inventory levels, reduce carrying costs, prevent stockouts, or classify products by inventory priority — even if they say 'we have too much stock', 'we keep running out of bestsellers', 'how much safety stock do we need', or 'which products should we focus on'.