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Found 307 Skills
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpoin...
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.
AD Certificate Services attack playbook. Use when targeting misconfigured AD CS for privilege escalation via ESC1-ESC13 template abuse, NTLM relay to enrollment, CA officer abuse, and certificate-based persistence.
Broadcast fire-and-forget events through the iii-pubsub worker. Use when publishing topic events to multiple subscribers without queue persistence, retries, FIFO ordering, or dead-letter handling.
Audit an AI agent skill for security risks before installing or trusting it. Runs a deterministic scanner (regex patterns, Python AST analysis, source-to-sink taint tracking, and YARA signatures) and then reasons about intent — catching prompt injection, credential exfiltration, persistence, memory poisoning, malicious code, supply-chain risks, and description-vs-behavior mismatch. Make sure to use this skill whenever the user wants to scan, audit, vet, review, or check the safety of a skill, plugin, SKILL.md, or agent tool — whether it is a local folder, a zip/.skill file, or a cloned repo — and whenever someone asks "is this skill safe to install?".
Production-tested setup for Zustand state management in React applications with TypeScript. This skill provides comprehensive patterns for building scalable, type-safe global state. Use when: setting up global state in React, migrating from Redux or Context API, implementing state persistence with localStorage, configuring TypeScript with Zustand, using slices pattern for modular stores, adding devtools middleware for debugging, handling Next.js SSR hydration, or encountering hydration errors, TypeScript inference issues, or persist middleware problems. Prevents 5 documented issues: Next.js hydration mismatches, TypeScript double parentheses syntax errors, persist middleware export errors, infinite render loops, and slices pattern type inference failures. Keywords: zustand, state management, React state, TypeScript state, persist middleware, devtools, slices pattern, global state, React hooks, create store, useBoundStore, StateCreator, hydration error, text content mismatch, infinite render, localStorage, sessionStorage, immer middleware, shallow equality, selector pattern, zustand v5
End-to-end workflow for TypeScript db-core modules: discover schema/model inputs, run DB/document/DAO generation, scaffold DB/document converters, and scaffold procedures with capability-aware validation and safe persistence boundaries. Use when the user asks to regenerate db-core artifacts, generate beans/DAOs from schemas, scaffold or update converters, or scaffold procedure CRUD methods. Trigger keywords: db-core, Db beans, DAO, converter, procedure.
Production-tested setup for Zustand state management in React. Includes patterns for persistence, devtools, and TypeScript patterns. Prevents hydration mismatches and render loops.
Advanced window and view management patterns for Electrobun desktop applications. This skill covers multi-window architectures, BrowserView for embedded webviews, window lifecycle management, window orchestration, tab systems, and complex window hierarchies. Use this skill when building applications with multiple windows, implementing browser-like tab interfaces, managing parent-child window relationships, creating floating panels or toolbars, implementing picture-in-picture modes, managing window state persistence across sessions, or building applications that require sophisticated window coordination. Triggers include "multiple windows", "tab system", "BrowserView", "window orchestration", "floating window", "child window", "window state", "window manager", "multi-window app", or discussions about complex window management in Electrobun desktop applications.
Implements Syncfusion Angular DataManager for local/remote binding, CRUD, querying, caching, and middleware. Supports JsonAdaptor, ODataAdaptor, ODataV4Adaptor, UrlAdaptor, WebApiAdaptor, WebMethodAdaptor, RemoteSaveAdaptor, GraphQLAdaptor, CustomDataAdaptor, and CustomAdaptor. Covers Query class, filtering, sorting, paging, grouping, persistence, offline mode, caching, and error handling.
Ouroboros specification-first AI development — the complete system. Socratic interviewing crystallizes vague ideas into immutable specs (Ambiguity ≤ 0.2) before any code is written. Nine Minds agents (socratic-interviewer, ontologist, seed-architect, evaluator, contrarian, hacker, simplifier, researcher, architect) execute the Double Diamond. Ralph mode loops with state persistence until verification passes — the boulder never stops. Use when user says "ralph", "ooo", "ooo interview", "ooo seed", "ooo run", "ooo evaluate", "ooo evolve", "ooo unstuck", "ooo status", "ooo ralph", "stop prompting", "start specifying", "specification first", "socratic interview", "don't stop", "must complete", "keep going", or "the boulder never stops".
Use when the user needs self-hosted or local Chroma for semantic search, including `ChromaClient`, `HttpClient`, or Python `EphemeralClient`, local persistence, Docker or `chroma run`, or OSS Chroma without Chroma Cloud features.