Converge on a single recommended solution after brainstorming options. Use when you have multiple candidate approaches and need to analyze trade-offs, select one, and define decision criteria before planning.
Use after opportunities are defined to generate and evaluate multiple product solution concepts before validating assumptions. Triggers when you need a set of distinct solution options tied to outcomes and opportunities.
Use when running or maintaining an Opportunity Solution Tree (OST) workflow with a lightweight graph store and CLI. Provides a single entry skill that routes to outcome, opportunity, solution, and assumption/experiment phases via progressive disclosure.
Generate multiple viable solution options after research is complete, before converging on a single approach. Use when you need to explore the solution space, ask clarifying questions, and produce 3-5 distinct options to consider.
Use when ready to publish a new version. Triggers on "release", "publish", "ship it", or version bump requests. Runs quality checks, bumps version, tags, and creates GitHub release.
Skriv, omskriv eller redigér tekst i Kaspers personlige skrivestil. Brug når brugeren beder om at skrive "som Kasper" eller ønsker stil-efterligning/tilpasning baseret på konkrete skriveeksempler.
Use when solution space exploration is complete and you're ready to create an implementation plan. Enforces "simple over easy" - the fundamentally right solution, not the path of least resistance. Triggers after /design-solution, when a solution has been chosen, or when asked to "make a plan" or "create a plan".
Use when work is complete and ready to commit. Triggers after code review passes, when asked to "commit", "save this", or "wrap up". Runs quality checks, updates changelog, creates commit.
Use after outcomes are defined to discover opportunities, unmet needs, market gaps, or JTBD insights before choosing solutions.
Use after solution concepts exist to surface and prioritize assumptions behind outcomes, opportunities, or solution ideas and design experiments to test them.
Use when documentation needs to be updated, clarified, or reorganized to better serve users' jobs-to-be-done with low cognitive load and high signal.
Debug Maven Surefire unit tests by running them in JDWP "wait for debugger" mode (`-Dmaven.surefire.debug`) and attaching to the forked test JVM using **jdb** (preferred for CLI/agent debugging), IntelliJ, or VS Code. Use when asked to debug/step through a failing JUnit test, attach a debugger to a Maven test run, or run `mvn test -Dtest=Class[#method]` suspended on a port (including multi-module `-pl` runs). The JVM will block at startup until a debugger attaches; the agent should attach with `jdb -attach <host>:<port>` and drive the session from the terminal.
Run Maven tests in this repo with a consistent workflow (module clean, root -Pquick clean install to refresh .m2_repo, then module verify or a single test class/method). Use when asked to run tests/verify in the rdf4j multi-module build or when the user says mvnf.
This skill should be used when the user asks to "generate SEO report", "performance report", "traffic report", "SEO dashboard", "report to stakeholders", "show me the numbers", "monthly SEO report", or "present SEO results to my boss". Generates comprehensive SEO and GEO performance reports combining rankings, traffic, backlinks, and AI visibility metrics. Creates executive summaries and detailed analyses for stakeholder reporting. For detailed rank tracking, see rank-tracker. For link-specific analysis, see backlink-analyzer.
This skill should be used when the user asks to "optimize entity presence", "build knowledge graph", "improve knowledge panel", "entity audit", "establish brand entity", "Google does not know my brand", "no knowledge panel", or "establish my brand as an entity". Works standalone with public search and AI query testing; supercharged when you connect ~~knowledge graph + ~~SEO tool + ~~AI monitor for automated entity analysis. For structured data implementation, see schema-markup-generator. For content-level AI optimization, see geo-content-optimizer.
This skill should be used when the user asks to "analyze competitors", "competitor SEO", "who ranks for", "competitive analysis", "what are my competitors doing", "what are they doing differently", "why do they rank higher", or "spy on competitor SEO". Analyzes competitor SEO and GEO strategies including their ranking keywords, content approaches, backlink profiles, and AI citation patterns. Reveals opportunities to outperform competition. For content-focused gap analysis, see content-gap-analysis. For link profile specifics, see backlink-analyzer.
This skill should be used when the user asks to "optimize for AI", "get cited by ChatGPT", "appear in AI answers", "GEO optimization", "generative engine optimization", "Google AI Overview optimization", "get mentioned by Perplexity AI", "appear in Gemini answers", "AI does not mention my brand", "make content AI-quotable", or "increase AI citation frequency". Optimizes content to increase citation frequency across AI systems: ChatGPT (Browse), Claude, Perplexity AI, Google AI Overviews, and Google Gemini. Adds quotable statements, structured Q&A, precise statistics with sources, expert attribution, and FAQ schema. Uses CORE-EEAT GEO-First items (C02, C09, O03, R01–R05, E01) as optimization targets. Produces a GEO score, rewritten content sections, and a citation-optimization checklist. For SEO-focused writing, see seo-content-writer. For entity and brand AI presence, see entity-optimizer.
This skill should be used when the user asks to "audit page SEO", "on-page SEO check", "SEO score", "page optimization", "what SEO issues does this page have", "what is wrong with this page SEO", "score my page", or "why is this page not ranking". Performs comprehensive on-page SEO audits to identify optimization opportunities including title tags, meta descriptions, headers, content quality, internal linking, and image optimization. For server, speed, and crawl issues, see technical-seo-checker. For full EEAT content quality scoring, see content-quality-auditor.
This skill should be used when the user asks to "analyze search results", "SERP analysis", "what ranks for", "SERP features", "why does this page rank", "what is on page one for this query", "who ranks for this keyword", or "what does Google show for". Analyzes search engine results pages (SERPs) to understand ranking factors, SERP features, user intent patterns, and AI overview triggers. Essential for understanding what it takes to rank. For tracking rankings over time, see rank-tracker. For keyword discovery, see keyword-research.
This skill should be used when the user asks to "write SEO content", "create a blog post", "write an article", "content writing for SEO", "draft optimized content", "write a how-to guide", "create a product description", "write a landing page", "SEO copywriting", "draft content targeting [keyword]", or "write 2000-word article about [topic]". Creates keyword-optimized content using a 12-step workflow: CORE-EEAT pre-write checklist, keyword integration, title optimization (5 formula options), meta description, H1/H2/H3 hierarchy, featured snippet targeting, internal/external linking, and readability enhancement. Produces full drafts with embedded SEO elements, title variants, meta description, FAQ section with schema, and a self-scored CORE-EEAT checklist. For AI-citation optimization, see geo-content-optimizer. For updating existing content, see content-refresher.