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Found 765 Skills
AI-enhanced LaTeX Example Intelligent Generator, achieving organic integration of AI and hard-coding. AI handles "semantic understanding" (analyzing chapter themes, inferring resource relevance, generating coherent narratives), while hard-coding is responsible for "structure protection" (format validation, hash verification, access control). It applies to scenarios where users request "filling example content/generating examples/supplementing LaTeX examples".
Use when running tests to validate implementations, collecting test evidence, or debugging failures. Load in TEST state. Covers unit tests (pytest/jest), API tests (curl), browser tests (Claude-in-Chrome), database verification. All results are code-verified, not LLM-judged.
Generate interactive presentation slides using React + Tailwind, and export to standalone single-file HTML. Triggers on keywords like "slides", "presentation", "PPT", "demo", "benchmark", or when user requests export. Uses agent-browser skill for browser verification before export (install with `npx skills add vercel-labs/agent-browser` if not available).
Testing Inertia Rails responses with RSpec and Minitest: component assertions, prop matching, flash verification, deferred props, and partial reload helpers. Use when writing controller specs, request specs, or integration tests for Inertia pages. ALWAYS use matchers (render_component, have_props, have_flash), NOT direct access (inertia.component, inertia.props). CRITICAL: after POST/PATCH/DELETE with redirect, MUST call follow_redirect! before asserting flash or props — without it you're asserting against the 302, not the Inertia page. Setup: require 'inertia_rails/rspec'.
Guidance for implementing Adaptive Rejection Sampling (ARS) algorithms. This skill should be used when implementing rejection sampling methods, log-concave distribution samplers, or statistical sampling algorithms that require envelope construction and adaptive updates. It provides procedural approaches, performance considerations, and verification strategies specific to ARS implementations.
Guide for designing DNA insertion primers for site-directed mutagenesis (SDM) using Q5 or similar kits. This skill should be used when tasks involve inserting DNA sequences into plasmids, designing mutagenesis primers, or working with PCR-based insertion methods. Provides verification strategies, common pitfalls, and procedural guidance for correct primer design.
Comprehensive paid advertising audit and optimization for any business type. Performs full multi-platform audits (Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads), single-platform deep analysis, conversion tracking health checks, creative quality assessment, budget allocation optimization, bidding strategy evaluation, and compliance verification. Industry detection for SaaS, e-commerce, local service, B2B enterprise, info products, mobile app, real estate, healthcare, finance, and agency. Triggers on: "ads", "PPC", "paid advertising", "Google Ads", "Meta Ads", "Facebook Ads", "LinkedIn Ads", "TikTok Ads", "Microsoft Ads", "Bing Ads", "ad audit", "campaign audit", "ROAS", "conversion tracking", "creative fatigue", "bid strategy".
Guide users step-by-step through manually testing whatever is currently being worked on. Use when asked to "test this", "verify it works", "let's test", "manual testing", "QA this", "check if it works", or after implementing a feature that needs verification before proceeding.
Guidance for working with the Beltic KYA (Know Your Agent) ecosystem - a credential-based trust framework for AI agents. Use when: (1) Working in any Beltic repository (beltic-spec, beltic-cli, beltic-sdk, fact-python, kya-platform, wizard, nasa), (2) Implementing agent credential signing/verification, (3) Using @belticlabs/kya SDK or beltic-sdk Python, (4) Understanding agent safety certification, (5) Working with verifiable credentials for AI. Triggers on: Beltic CLI commands, agent credentials, HTTP message signatures (RFC 9421), safety scores, KYB tier verification, trust chain validation.
Iteratively write academic documents (paper sections, research proposals, technical documents) with quality improvement loop. Uses academic-planner for structure design and academic-reviewer for quality evaluation. Ensures no hallucinations through fact verification.
E2E testing expert for Tauri applications using Tauri MCP server. Use when testing running Tauri apps - session management, webview interaction, IPC verification, screenshot capture, and debugging. ALWAYS use tauri_* tools, NEVER Chrome DevTools MCP for Tauri apps.
Use when planning or designing features and need to understand current codebase state, find existing patterns, or verify assumptions about what exists; when design makes assumptions about file locations, structure, or existing code that need verification - prevents hallucination by grounding plans in reality