Results for “markdown”

Write growth logs that extract reusable patterns from complex tasks, failures, and learning moments, using a structured template and quality checklist.

Professional CV and resume builder transforming career narratives into ATS-optimized, multi-format resumes. Integrates with career-biographer for data and competitive-cartographer for positioning. Generates PDF, DOCX, LaTeX, JSON Resume, HTML, and Markdown. Activate on 'resume', 'CV', 'ATS optimization', 'job application'. NOT for cover letters, portfolio websites (use web-design-expert), LinkedIn optimization, or interview preparation.

Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and citation capsules. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Research-driven SEO content writer that produces publication-ready markdown articles built around search intent, verified claims, and original value. Use this skill whenever the user asks for a blog post, article, long-form content, "content for our site", a post targeting a keyword, a content refresh or audit of an existing article, or anything meant to be published on a website — even if they never say "SEO". Also use it when the user mentions keywords, search rankings, organic traffic, content marketing, meta descriptions, keyword cannibalization, or asks to "write something about X for the blog". If a piece of writing is destined for the web and could benefit from search visibility, use this skill.

Use this skill whenever LMX is used, produced, reviewed, migrated, or modified. This includes composing campaigns, loops, lifecycle emails, or email-message bodies for the Loops editor or Content API. LMX (Loops Markup Language) is the format used for Loops email content. Trigger on phrases like "create a campaign", "generate an email", "write a welcome email", "draft a lifecycle email", "build an email template", "create an onboarding email", "copy this into LMX", "migrate this email", "convert this email to LMX", "design a new Loops email", "use imagegen for a Loops email", "use gpt-image for an LMX reference", "visual reference for a Loops email", "LMX", "Loops email", or any request to produce, copy, migrate, convert, review, or modify email body content intended for Loops. For net-new emails or major visual redesigns, follow this skill's Net-New Email Design Flow before generating or sourcing new visual assets. Source copy, existing HTML, MJML, Markdown, screenshots, and migration instructions do not byp