557 skills · sorted by relevance
Use when the user asks to "analyze competitors" or "竞品分析"; benchmarks competitor keywords, content, backlinks, AI citations, and traffic share into strengths, weaknesses, and an action plan. Not for a pairwise topic-coverage gap map — use content-gap-analysis. 竞品分析/竞争对手
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End-to-end SEO operations for B2B SaaS organic visibility. Use this skill when you need keyword research, technical SEO audits, content optimization, link building strategy, international expansion, AI/AEO optimization, schema markup, Core Web Vitals improvements, and organic traffic growth planning. Also triggers on: SEO, keyword research, technical SEO, link building, content optimization, international SEO, hreflang, x-default, multilingual site, translated pages not ranking, our German site gets no traffic, language switcher, auto-redirect by country, machine translation SEO, content parity, ccTLD vs subfolder, AI search, AEO, GEO, Core Web Vitals, schema markup, organic traffic, G2 listing, Capterra, TrustRadius, review-platform category page, best software roundup, listicle placement, directory submissions, do we need a Google Business Profile in [country], local SEO with no office, Google Business Profile eligibility, virtual office address SEO, coworking address business profile, business profile suspended, NAP consistency, local citations for SaaS, LocalBusiness schema.
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Helps an AI assistant write, structure, and edit articles in the encyclopedic style of Wikipedia — neutral tone, lead section, summary style, inline citations, no peacock/weasel/persuasive language, and the stub→FA quality ladder. Also covers Simple English Wikipedia rules. MADE BY SQERSTERS
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This is the core skill for the deep research and writing tool—combining AI-driven deep research with well-formatted written outputs. Every document produced is backed by comprehensive literature search and verified citations through the research-lookup skill.
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Derive slices from specs, order by dependencies, write acceptance criteria with citations, and finalize phase/progress artifacts
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Run Tavily's multi-source research workflow for comparisons, market analysis, literature-oriented exploration, or detailed cited reports. Use only when bounded search and extraction are insufficient.
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Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, latest/current/default-model prompting guidance, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.
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Review final-assignment materials for requirements, citations, AI-use disclosure, and data-analysis completeness.
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Current external research using available web tools, primary sources where possible, links/citations, date awareness, synthesis, and unresolved uncertainty.
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Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
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Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.
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Detects content similarity, verifies standardized citations and abbreviations, and flags potential academic integrity risks; use it before submission, during academic writing QA, or for compliance reviews.
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Creates high-quality content (blog posts, tweets, newsletters, documentation) that matches the user's writing style and voice. Performs web research to find citations and supporting evidence. Use when user requests blog posts, marketing content, newsletters, tweets, or any written content that should sound authentic and be well-researched.
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ALWAYS use this skill whenever you would otherwise ask the user a question in free-form chat -- for clarifications, confirmations (especially destructive actions), missing parameters, multiple-choice decisions, or structured form input. Elicitations are routed through the Unique AI Platform UI via `unique-cli elicit create` + `elicit wait` (the default polling pattern) or a single supervised `unique-cli elicit ask` call (only when your agent instructions say your environment supervises the wait) so the user gets a proper structured prompt and you get a structured answer back. Do NOT ask the user in plain chat when you can use this skill instead.
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SEO + GEO (AI-search) + brand-entity desk (Busabase App-in-Skill) — wired to Google Search Console for a dashboard over search analytics and an agent-prepared SEO opportunities review queue, plus an AI-visibility tracker (are we cited in ChatGPT / Perplexity / Gemini / Claude / Copilot answers), a GEO content-optimization queue gated by geo-qa, and an entity / knowledge-panel readiness checklist. Use when the user invokes $kelly-seo or /kelly-seo, mentions SEO, Google Search Console, GSC, search analytics, search performance, queries, keywords, rankings, positions, impressions, clicks, CTR, striking-distance queries, title/meta rewrites, content briefs, internal links, SEO opportunities review, GEO, generative engine optimization, AI search, AI visibility, being cited by AI answer engines, ChatGPT/Perplexity/Gemini/Claude/Copilot citations, brand entity, knowledge panel, Wikidata, schema.org, or entity readiness.
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Legal precedent App-in-Skill (Busabase-backed) desk for internal casebase search, local court-pattern analysis, similar-case packs, citations, and approval-gated research exports. Use when the user invokes $kelly-legal-precedent-desk, mentions 类案检索, 本地裁判尺度, 内部案例库查询, 案例查阅与收藏, precedent research, similar cases, legal research pack, or wants a Busabase-backed desk where lawyers review agent-prepared precedent findings before reuse.
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Searches across your Notion workspace, synthesizes findings from multiple pages, and creates comprehensive research documentation saved as new Notion pages. Turns scattered information into structured reports with proper citations and actionable insights.
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Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
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Deep literature review — PubMed, EuropePMC, bioRxiv preprints, citation networks, evidence synthesis. Disambiguates queries, runs collision-aware searches, grades evidence T1-T4, and produces structured reports. Use for systematic literature review, meta-analysis evidence collection, and detailed answer-with-citations workflows.
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Find external documentation, web sources, or remote code with citations. Local code navigation uses the configured code tools.
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Claude API (platform.claude.com) の Messages API リファレンス。 streaming (SSE), thinking (adaptive) / preserved thinking / effort, prompt caching, context editing, compaction (on-demand / threshold), structured outputs, Message Batches, token counting, vision / PDF, Files API, citations, embeddings (Voyage AI), errors, rate limits, beta headers, Bedrock / Vertex AI / Foundry 経由アクセス。
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Use when the user is explicitly working with Quarto, .qmd files, _quarto.yml, Quarto projects, or Quarto features such as callouts, cross-references, citations, Mermaid diagrams, extensions, websites, books, presentations, and reports. Also use for explicit migration from or comparison with R Markdown, bookdown, blogdown, xaringan, distill, or Jupyter notebooks to Quarto. Do not use for general R Markdown or related-format questions unless Quarto or migration to Quarto is explicitly mentioned.
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Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
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Use when the user wants a code review of an explicit range or set of files — correctness, security, performance, conventions, tests — with stable findings (CR-nnn, BLOCKER..INFO) and rule citations — 'revisar os últimos commits', 'code review da feature X', 'review base..HEAD'. Plans a REPORT-mode review (no code changes, no commit). Do NOT use to fix code (feat-feature / feat-quick), to write tests (feat-test) or for UI/UX design critique.
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