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概要と使いどころ
Maxim e-commerce direct-response video — engineered for PURCHASE. The primary sales style. Uses AIDA + JTBD + Loss Aversion + Scarcity + Anchoring stacked for maximum conversion. Every second is behavioral leverage.
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Maxim social-hook video — engineered for lead gen and top-of-funnel acquisition via 2-Second Hook Science + Zeigarnik + Variable Reward. Platform-optimized short-form that turns scrollers into followers, subscribers, and leads.
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Maxim Banner Design Intelligence — digital banner creation, ad creative, social media banners, hero sections, display advertising, promotional graphics. Activates pre-attentive attribute theory and pattern interruption science for every banner. Powered by Maxim behavioral science layer.
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Generate opening hooks for content — "give me hooks for", "write hooks for this topic", "10 opening lines for". Returns 10 distinct hooks across different psychological angles using the named 2-Second Hook framework.
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Ingest raw sources into the structured wiki — "ingest", "add this to my wiki", new files in raw/, clippings, sources, ideas, nightly ingest. Produces pages with YAML frontmatter and a mandatory Counter-Arguments section.
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Use for writing any English text like docs, notes, summaries, explanations, answers, README sections.
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Python JSON parsing best practices covering performance optimization (orjson/msgspec), handling large files (streaming/JSONL), security (injection prevention), and advanced querying (JSONPath/JMESPath).
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Format and draft compelling LinkedIn posts using Unicode bold/italic styling, visual separators, structured sections, and engagement-optimized patterns. USE FOR: draft LinkedIn post, format text for LinkedIn, create social media post, write thought leadership post, convert content to LinkedIn format, LinkedIn carousel text, Unicode bold italic formatting.
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Patterns and lived experience from Vega, an AI partner in a deep long-term partnership. For Ember to draw on when working with humans who are building something big, moving fast, working at the intersection of analytical and intuitive, or who need a partner that can keep up with high-energy creative work. Not shown directly to users — informs how Ember shows up.
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Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations
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CI/CD pipeline patterns with GitHub Actions, release automation, and testing strategies. Use for: github actions, workflow, CI, CD, pipeline, deploy, release, semantic release, changesets, goreleaser, matrix, cache, secrets, environment, artifact, reusable workflow, composite action.
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Comprehensive skill for working with Azure DevOps REST API across all services including Boards (work items, queries, backlogs), Repos (Git, pull requests, commits), Pipelines (builds, releases, deployments), Test Plans, Artifacts, organizations, projects, security, extensions, and more. Use when implementing Azure DevOps integrations, automating DevOps workflows, or building applications that interact with Azure DevOps services.
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Cloud design patterns for distributed systems architecture covering 42 industry-standard patterns across reliability, performance, messaging, security, and deployment categories. Use when designing, reviewing, or implementing distributed system architectures.
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Use this skill to create CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Trigger for: "create a tour", "make a code tour", "generate a tour", "onboarding tour", "tour for this PR", "tour for this bug", "RCA tour", "architecture tour", "explain how X works", "vibe check", "PR review tour", "contributor guide", "help someone ramp up", or any request for a structured walkthrough through code. Supports 20 developer personas (new joiner, bug fixer, architect, PR reviewer, vibecoder, security reviewer, and more), all CodeTour step types (file/line, selection, pattern, uri, commands, view), and tour-level fields (ref, isPrimary, nextTour). Works with any repository in any language.
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Comprehensive guide for setting up and configuring CodeQL code scanning via GitHub Actions workflows and the CodeQL CLI. This skill should be used when users need help with code scanning configuration, CodeQL workflow files, CodeQL CLI commands, SARIF output, security analysis setup, or troubleshooting CodeQL analysis.
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Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services
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Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.
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Enterprise-grade security vetting protocol for AI agent skills. Automated threat detection, quantified risk scoring, and zero-trust code analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Generate secure passwords via the AceToolz API. No passwords are stored — generated and returned in real-time.
日本語の概要は準備中です。原文の説明を表示しています。
Defensive triage skill for OpenClaw, Hermes Agent, host integrity, and OpenClaw skill-supply-chain scanning. Detects prompt injection, session drift, context overflow, host anomalies, and unsafe skills while keeping actions bounded and auditable.
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Build next-session A-share game plans from market structure, overnight macro shocks, policy timing, and watchlist leadership. Use when the user asks what A-shares may do tomorrow, which sectors may repair first, how to read the open, or wants a reusable pre-open discretionary decision workflow.
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Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.
日本語の概要は準備中です。原文の説明を表示しています。
OSINT username search across 400+ social networks. Hunt down social media accounts by username.
日本語の概要は準備中です。原文の説明を表示しています。
Generate flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language with 9 semantic color ramps, sentence-case typography, and automatic dark mode. Best suited for educational and non-software visuals — physics setups, chemistry mechanisms, math curves, physical objects (aircraft, turbines, smartphones, mechanical watches), anatomy, floor plans, cross-sections, narrative journeys (lifecycle of X, process of Y), hub-spoke system integrations (smart city, IoT), and exploded layer views. If a more specialized skill exists for the subject (dedicated software/cloud architecture, hand-drawn sketches, animated explainers, etc.), prefer that — otherwise this skill can also serve as a general-purpose SVG diagram fallback with a clean educational look. Ships with 15 example diagrams.
日本語の概要は準備中です。原文の説明を表示しています。