「research」の検索結果

Use when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or voice-of-customer insights from public social posts and videos.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants a social listening report about what people are saying about a brand, person, product, topic, category, or niche across public social platforms. Produces cited themes, sentiment caveats, notable posts, and recommended actions.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to find posts, videos, reels, shorts, tweets, or social content that overperformed versus a creator, brand, or competitor baseline. Finds outliers, explains why they worked, extracts hooks and formats, and produces a practical swipe file.

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Scrape and extract public data from 27+ social media platforms using the ScrapeCreators REST API. Covers TikTok, Instagram, YouTube, LinkedIn, Facebook, Twitter/X, Reddit, Threads, Bluesky, Pinterest, Snapchat, Twitch, Kick, Truth Social, TikTok Shop, Google, and link-in-bio services (Linktree, Komi, Pillar, Linkbio, Linkme, Amazon Shop). Use when the user asks to scrape, fetch, extract, search, or look up social media profiles, posts, videos, reels, comments, transcripts, followers, ads, hashtags, trending content, or engagement metrics from any social platform. Also use when user mentions ScrapeCreators, social media API, ad library, or creator data.

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Use when the user wants to analyze a creator, influencer, founder, or brand social account and understand positioning, content pillars, outlier posts, hooks, format choices, audience reaction, and what can be copied or tested.

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Use when the user wants to discover trending social topics, hashtags, sounds, posts, reels, shorts, creators, or formats in a niche. Searches public trend and discovery endpoints, ranks evidence, and turns trends into practical content angles.

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Use when the user wants to summarize, analyze, or repurpose transcripts from TikTok, Instagram, YouTube, Facebook, X/Twitter, LinkedIn, Rumble, or Reddit video posts. Extracts hooks, claims, quotes, content atoms, themes, and reusable scripts.

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Operate an explicitly activated LoopX Material Lifecycle for a connected project. Use for material-store inventory, lossless migration, candidate/archive transitions, exact-read-backed ranking, ranked-entry rebuilds, bounded Explore intake, owner-gated apply, rollback, and audit. Do not use for ordinary one-off reading or research when the project has not activated Material Lifecycle.

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Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.

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Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.

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Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.

日本語の概要は準備中です。原文の説明を表示しています。

Autonomous performance optimization: research, PoC, benchmark, implement, review, PR

日本語の概要は準備中です。原文の説明を表示しています。

Update durable docs when explicitly requested or when current work changes behavior, exposes stale instructions, establishes an operational pattern, or yields reusable research guidance.

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Programmatic SEO planning and audit: building or evaluating large sets of template-generated pages that target long-tail query patterns (e.g. "[service] in [city]", "[product] vs [product]", "[tool] for [use-case]"). Covers data-source and template design, thin/duplicate-content and doorway-page risks, per-page uniqueness and value thresholds, internal linking and hubs, indexation management (publish vs. noindex), and scaling without a manual action. Use whenever the user wants to generate many pages from a template/dataset, build location/comparison/use-case pages at scale, or asks why generated pages aren't indexing. Trigger on: "programmatic SEO", "pSEO", "generate pages at scale", "templated pages", "location pages at scale", "comparison pages", "[city] pages", "my generated pages aren't indexed", "doorway pages", "scale content". For one-off content use /content-writer; for keyword discovery use /keyword-research.

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Competitor page gap analysis — take a query you want to win and the pages currently outranking you, and produce a concrete brief on what to add or change to compete. Compares content depth and coverage (subtopics they cover that you don't), structure (headings, format, tables, media), search-intent match, E-E-A-T signals, schema/rich-result eligibility, internal linking, and on-page optimization — across your page vs. the top-ranking competitors. Use this skill whenever the user wants to know why a competitor outranks them on a specific query, what a top-ranking page does better, a content-gap analysis against specific competitor URLs, or a brief to beat a specific SERP. Trigger on: "why does competitor X outrank me", "content gap analysis", "competitor page analysis", "what does the top result have that I don't", "how do I beat this page", "analyze competitor pages", "SERP gap", "compete for [keyword]". For seed keyword discovery use /keyword-research; for a content calendar use /content-planner.

日本語の概要は準備中です。原文の説明を表示しています。

Full SEO audit combining Google Search Console, URL Inspection API, PageSpeed Insights, a technical crawl, keyword research, and metadata, schema, search intent and Core Web Vitals checks. Surfaces quick wins, diagnoses traffic drops and content gaps, and produces an actionable 30-day plan. Use whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, search visibility, technical SEO, URL indexing, or LCP, INP, CLS or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "crawl errors", "content strategy", "keyword cannibalization", "search intent", "schema markup", "structured data", "URL inspection", "page speed", "performance score", "core web vitals", "lighthouse", or any organic search question. If in doubt, trigger.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze repository structure, patterns, conventions, and documentation for understanding a new codebase

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AI-powered web search, research, and reasoning via Perplexity

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Document codebase as-is with thoughts directory for historical context

日本語の概要は準備中です。原文の説明を表示しています。

Formal theorem proving with research, testing, and verification phases

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Research-to-implement pipeline chaining 5 MCP tools with graceful degradation

日本語の概要は準備中です。原文の説明を表示しています。

Migration workflow - research → analyze → plan → implement → review

日本語の概要は準備中です。原文の説明を表示しています。

Provides adversarial code comprehension for security research, mapping architecture, tracing data flows, and hunting vulnerability variants to build ground-truth understanding before or alongside static analysis.

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ACTIVATES ONLY on an explicit user request for the ulw-plan workflow: the user themselves saying ulw-plan, ulw plan, /skill:ulw-plan, or asking in their own words for a work plan before coding. NEVER self-activates: a bare ulw/ultrawork run, an agent-side routing decision, or reading this file is not a request, and the plan-gated reviewers (metis/momus) stay locked without a user request plus a written .omo/plans plan file. Explore-first planning consultant (Prometheus) that grounds in the codebase, asks only the forks exploration cannot resolve - or researches them to best practice when the intent is fuzzy - waits for explicit approval, then writes ONE decision-complete work plan a worker executes with zero further interview. Triggers: ulw-plan, ulw plan, plan this, make a plan, plan before coding, interview me, break this down, start planning, plan mode.

日本語の概要は準備中です。原文の説明を表示しています。