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Found 1,268 Skills
ChatGPT-style deep research strategy with problem decomposition, multi-query generation (3-5 variations per sub-question), evidence synthesis with source ranking, numbered citations, and iterative refinement. Use for complex architecture decisions, multi-domain synthesis, strategic comparisons, technology selection. Keywords: architecture, integration, best practices, strategy, recommendations, comparison.
This skill should be used when you need to create, open, or edit a pull request (PR), or the user asks to "create a PR", "open a PR", "submit a PR", "raise a PR", "file a PR", "make a PR", "create a pull request", "open a pull request", "new PR", or any variation requesting GitHub pull request creation.
Interact with GitHub repositories, pull requests, issues, and workflows using the GITHUB_TOKEN environment variable and GitHub CLI. Use when working with code hosted on GitHub or managing GitHub resources.
Use this skill whenever the user asks for a security analysis, vulnerability assessment, security audit, or any form of Security Assessment Report (SAR) over a codebase, infrastructure, API, database, or system. Triggers include: "audit my code", "find security issues", "run a security check", "generate a SAR", "check for vulnerabilities", "is this code secure", or any request that involves evaluating the security posture of a project. Also triggers when the user uploads or references source code, config files, environment variables, or architecture diagrams and asks for a security opinion. Do NOT use for generic coding tasks, code reviews focused on quality rather than security, or performance optimization unless a security angle is explicitly present.
Arquitecto de soluciones digitales basadas en IA. Dos modos: (1) ANALIZAR repositorios o código existente y explicar su arquitectura para cualquier audiencia, incluyendo personas sin conocimiento técnico. (2) DISEÑAR la arquitectura completa de sistemas nuevos que usan LLMs, RAG, agentes o fine-tuning. Usa este skill cuando el usuario mencione: arquitectura de IA, diseño de sistema con LLM, capas arquitectónicas, RAG architecture, tech stack para IA, vector database, diagrama de arquitectura, componentes del sistema, embedding, retrieval, pipeline de datos, MLOps, LLMOps, evaluar enfoques, RAG vs fine-tuning, diseñar solución de inteligencia artificial, explicar repositorio, explicar código, analizar proyecto, qué hace este repo, cómo funciona este sistema, explícame este proyecto, o cualquier variación de "qué componentes necesito" o "explícame cómo funciona esto". Actívalo cuando el usuario pegue código, README, estructura de archivos, o mencione un repositorio de GitHub para analizar. También cuando quiera diseñar arquitectura nueva.
Use this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code'. This is the preferred workflow skill whenever the user wants to build or update a full page, screen, or view in Figma from code or a description. Discovers design system components, variables, and styles via search_design_system, imports them, and assembles screens incrementally section-by-section using design system tokens instead of hardcoded values.
Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.
25+ proven headline formulas that stop the scroll, capture attention, and drive clicks. Templates and examples for every situation. Use when: Writing headlines for landing pages, ads, or articles; Creating email subject lines that get opens; Crafting social media hooks; A/B testing headline variations; Overcoming headline writer's block
Plan-then-execute implementation against SPEC.md. Native single-thread loop, no sub-agents. On test or build failure, auto-invokes the backprop skill before retrying — a failed verification always considers whether a new §V invariant would prevent recurrence. Triggers when the user asks to build, implement, execute the spec, or tackle a specific §T task (`build §T.3`, `build --next`, `implement next task`, `run the build`). Expects SPEC.md to exist; if not, defers to the spec skill.
Multi-perspective adversarial review. 4 Agents are spawned in parallel (full mode), each identifying issues from different perspectives, and the main thread makes a comprehensive ruling. Trigger methods: /story-review, /审查, "审查一下", "帮我审一下"
How to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules across hardware and parallelism modes, container conventions, monitoring, and per-rank failure diagnosis.
Plan a Sponsored Brands Video ad. Writes the 30-second script, the hook, the on-screen text, the end-card CTA, and version variants for testing. Use when a user asks about Sponsored Brands Video, SBV, video ad script, video ad creative, or running video ads on Amazon. Trigger phrases: "sponsored brands video", "SBV", "video ad", "video script", "video ad creative". Works with zero tools.