「survey」の検索結果

Guides user research and research ops. Use when running interviews, usability tests, surveys, or synthesis to de-risk product decisions; not experiments or review mining.

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Audits whether scores, benchmarks, LLM judges, or surveys measure what we think. Use when a benchmark is saturated, a score unreliable, or judge agreement untrustworthy.

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。

Collecting user feedback via NPS surveys, review analysis, sentiment analysis, feedback classification, and insight extraction reports. Use when establishing feedback loops.

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。

When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers or wants to build systems to prevent it. For post-cancel win-back email sequences, see emails. For in-app upgrade paywalls, see paywalls.

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。

When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," or "find out why customers churn/convert/buy." Use for both analyzing existing research assets AND gathering new research from online sources. For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.

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 asks for a literature review, academic deep dive, research report, state-of-the-art survey, topic scoping, comparative analysis of methods/papers, grant background, or any request that needs multi-source scholarly evidence with citations. Also trigger proactively when a user question clearly requires academic grounding (e.g. "what's known about X", "compare approach A vs B in the literature", "summarize the field of Y"). Runs an 8-phase (Phase 0..7), script-driven research workflow across 7 federated sources (OpenAlex, arXiv, Crossref, PubMed, DBLP, bioRxiv, Exa) with optional Semantic Scholar / Brave MCP enrichment, with deduplication, transparent ranking, dual-backend citation chasing (OpenAlex + Semantic Scholar), self-critique, and structured report output with verifiable citations.

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。

Kundenforschung datensparsam und einwilligungsorientiert planen, durchführen und auswerten. Nutze diesen Skill für Interviewleitfäden, Umfragen, Usability-Tests, die Auswertung vorhandener Gespräche, Support-Tickets oder Bewertungen, und für Personas, Segmente und Jobs-to-be-Done. Klärt vorab Zweck, Rechtsgrundlage, Einwilligung, Aufzeichnung, Pseudonymisierung und Aufbewahrung, wertet nur innerhalb des Stichprobenrahmens aus und trennt Befund von Entscheidung. Beachtet DSGVO, BDSG und Beschäftigtendaten; Österreich und Schweiz werden getrennt behandelt.

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Read, study, and answer questions about long books and papers without loading the whole text into one context window, keeping page-anchored notes as a reusable workspace. Use whenever the user asks to read, study, summarize, analyze, review, or answer questions about a long book, textbook, PDF, EPUB, thesis, dissertation, survey paper, or any document of roughly 50+ pages, in any language (Vietnamese "đọc sách", "tóm tắt sách", "phân tích luận án"). Also use when a `{slug}-notes/` workspace from a previous session sits next to a source file and the user asks a follow-up question about that book. Not for short documents (under ~30 pages) that fit in context; read those directly.

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 French rental property investments with comprehensive financial modeling. Use when analyzing French properties, calculating mortgage payments, ROI, cash flow projections, or break-even analysis. Includes French-specific costs like arrangement fees (1%), registration fees (1.5%), survey fees (€750), and mandatory life insurance (0.4% annually).

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。

Product landscape reconnaissance — survey existing briefs, research, strategy, and team output before writing new briefs or dispatching specialists. Use when asked to "understand the product state", "what briefs exist", "what has the team produced", "orient me on this product", or before starting a new product initiative.

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。

Survey existing cloud cost controls — tagging coverage, alerting, and FinOps maturity. Use when asked to "audit our cost controls", "is our tagging complete", or "assess our FinOps maturity".

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。

Feedback synthesis — cluster support tickets, NPS verbatims, app store reviews, and churn surveys by theme, separate signal from noise, and produce an actionable insight report. Use when asked to "synthesize this feedback", "analyze support tickets", "what are users complaining about", "NPS analysis", "churn feedback synthesis", or "what's the feedback telling us".

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。

User research reconnaissance — survey existing personas, research docs, interview notes, and feedback artifacts to establish what is already known about users. Use when asked to "what research exists", "review existing personas", "what do we know about our users", or before starting new research or synthesis work.

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。

Survey open legal questions and research gaps in the project. Use when asked "what legal questions are open", "where are our research gaps", or "list unresolved legal issues".

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。

Survey all user-facing strings in a codebase — map coverage and find gaps. Use when asked "what user-facing strings do we have", "map our copy coverage", or "find hardcoded strings".

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。

Survey existing forecasting code or models in a codebase — find gaps, stale models, and missing validation. Use when asked "what forecasting models do we have", "audit our forecasts", or "find stale models".

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。

Survey a codebase for accessibility debt — missing ARIA, broken keyboard patterns, and contrast issues. Use when asked "how accessible is our codebase", "find accessibility debt", or "where are our a11y gaps".

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Searches and discovers academic papers across multiple sources (Semantic Scholar, arXiv, Tavily, Exa, Gemini deep research, AMiner, Google Scholar) with adaptive engine selection based on query type. Returns ranked, deduplicated results with metadata (authors, venue, year, citations, abstract, PDF link). Use when the user asks to find papers / literature / publications / preprints / references on a topic, search for related work, look up a specific paper by title or DOI or arXiv ID, find papers by an author, find recent SOTA / state-of-the-art work, survey a research area, or run a deep / comprehensive literature search with synthesis.

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。

A survey of the best-known active scientific controversies in nutrition — saturated fat and cardiovascular disease, dietary cholesterol, low-carb vs low-fat, ultra-processed foods, red meat and cancer, salt and blood pressure, and the replication status of popular single-nutrient claims. Use when a question asks whether a widely reported nutritional claim is settled, or when the department needs to distinguish "contested but plausible" from "settled" from "disproven."

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。

Field observation, data collection, and research methods for geographic inquiry. Covers site selection and sampling strategies, field observation techniques (landscape reading, transects, quadrats), survey and interview methods for human geography, GPS and field mapping, environmental monitoring and instrumentation, data recording and field notebooks, ethical considerations in fieldwork, and the integration of field data with GIS analysis. Use when planning geographic field research, designing data collection protocols, evaluating field evidence, or connecting field observations to broader geographic analysis.

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。

Observational cosmology from Hubble's law to the CMB. Covers redshift, Hubble expansion, the cosmological parameters, the cosmic microwave background, large-scale structure, galaxy rotation curves and dark matter, Type Ia SNe and dark energy, and the current state of Lambda-CDM. Use when reasoning about the large-scale universe, interpreting cosmological surveys, or teaching the Big Bang evidence chain.

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。

Survey the AI coding assistant and agentic tool ecosystem, assess skillsaw's competitive position, identify emerging patterns and missing capabilities, and produce a prioritized strategic report as a GitHub issue. Use when evaluating ecosystem trends and product gaps.

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。

When the user wants to optimize any form that is NOT signup/registration — including lead capture forms, contact forms, demo request forms, application forms, survey forms, or checkout forms. Also use when the user mentions "form optimization," "lead form conversions," "form friction," "form fields," "form completion rate," or "contact form." For signup/registration forms, see signup-flow-cro. For popups containing forms, see popup-cro.

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。

Advises on setting up and validating topic models for survey and experimental text. Covers the discovery-versus-measurement question, choosing STM, LDA, or BERTopic, preprocessing consequences, prevalence and content formulas, topic-count selection across coherence, exclusivity and FREX, held-out likelihood, and residuals, validation of topics against human judgment, robustness, and DA-RT-compliant reporting. Use when the user has open-ended responses or another corpus and asks what topics are present, how many topics to use, about STM, searchK, coherence, or FREX, or wants topic prevalence compared across treatment arms or countries. Fixed-codebook coding goes to text-classification.

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。