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Found 220 Skills
Complete SEO skill for technical audits (Core Web Vitals, site speed, crawlability/indexation, robots/sitemaps/canonicals, structured data, mobile, security, internal linking), SEO marketing strategy (keyword research, content planning, competitive analysis, E-E-A-T), operational workflows (cross-team collaboration, OKRs), link building, local SEO, international SEO (hreflang), and multi-platform SEO (Google, YouTube, Reddit, social). Updated for January 2026.
Paid advertising strategy for Google, Meta, TikTok, LinkedIn - campaign structure, bidding, audiences, creative, measurement, budget allocation, unit economics (CAC/LTV), revenue attribution, incrementality, payback period, and sales alignment.
Operational prompt engineering for production LLM apps: structured outputs (JSON/schema), deterministic extractors, RAG grounding/citations, tool/agent workflows, prompt safety (injection/exfiltration), and prompt evaluation/regression testing. Use when designing, debugging, or standardizing prompts for Codex CLI, Claude Code, and OpenAI/Anthropic/Gemini APIs.
Extract text/tables from PDFs, create formatted PDFs, merge/split/rotate, handle forms and metadata. Supports pdf-lib/pdfkit (Node.js) and pypdf/pdfplumber/ReportLab (Python).
Build accessible web applications following WCAG guidelines. Use when implementing ARIA patterns, keyboard navigation, screen reader support, or ensuring accessibility compliance. Triggers on accessibility, a11y, WCAG, ARIA, screen reader, keyboard navigation.
Use when designing go-to-market strategy, selecting GTM motion (PLG/sales-led), defining ICP, planning product launches, or implementing AI-powered GTM automation. Covers channel selection, growth loops, RevOps alignment, and market entry execution.
Risk-based quality engineering test strategy for software delivery. Use when defining or updating test strategy, selecting unit/integration/contract/E2E/performance/security coverage, setting CI quality gates and suite budgets, managing flaky tests and test data, and operationalizing observability-first debugging and release criteria.
Use when choosing or evaluating a startup revenue model, pricing/value metric, packaging/tier design, or calculating unit economics (LTV, CAC, payback, gross margin, NRR), including usage-based/credit/AI pricing and variable compute/COGS constraints.
End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (monitoring and retraining).
Configure AI coding agents to be honest, objective, and non-sycophantic. Use when the user wants to set up honest feedback, disable people-pleasing behavior, enable objective criticism, or configure agents to contradict when needed. Triggers on honest agent, objective feedback, no sycophancy, honest criticism, contradict me, challenge assumptions, honest mode, brutal honesty.
Route AI coding queries to local LLMs in air-gapped networks. Integrates Serena MCP for semantic code understanding. Use when working offline, with local models (Ollama, LM Studio, Jan, OpenWebUI), or in secure/closed environments. Triggers on local LLM, Ollama, LM Studio, Jan, air-gapped, offline AI, Serena, local inference, closed network, model routing, defense network, secure coding.
Build AI agents with Strands Agents SDK. Use when developing model-agnostic agents, implementing ReAct patterns, creating multi-agent systems, or building production agents on AWS. Triggers on Strands, Strands SDK, model-agnostic agent, ReAct agent.