314건 · 관련도순
Review module relationships and change history to identify structural improvements in a codebase. Receive ranked candidates with file references, suggested changes, and risks, plus a recommendation for where to start, without modifying code.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Plan user research, prepare interview guides, and organize findings into themes and recommendations. Choose methods suited to the question, such as interviews, surveys, or usability tests that examine how people use a design.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Turn interviews, surveys, usability notes, and customer feedback into shared themes, user groups, and prioritized recommendations. Findings include supporting quotes and participant counts, helping teams connect research evidence to concrete product improvements.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Route enterprise research questions to specialized skills for clinical studies, R&D finance, market research, or user research. Receive a concise digest of findings, next actions, output files, and assumptions that need human review.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Design SaaS cancellation flows, match retention offers to exit reasons, and prepare payment retry schedules and recovery emails. Get flow copy, survey options, email templates, and metrics for reviewing cancellations and failed payments.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Compare pricing models, analyze survey responses to estimate an acceptable price range, and design three product tiers. The skill explains trade-offs and flags weak tier structures, giving teams concrete inputs for a human pricing decision.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Turn survey responses, interviews, and other research data into three distinct user personas. Each profile explains the outcome users seek, their main difficulties, desired benefits, an unexpected behavioral insight, and how well the product meets their needs.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Use customer research, surveys, and usage data to define an ideal customer profile: the customers most likely to gain value, stay, and expand. Summarize their characteristics, buying behavior, goals, needs, and fit criteria to guide sales and marketing priorities.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Plan user research, prepare interview guides, and organize findings into themes and recommendations. Choose methods suited to the question, such as interviews, surveys, or usability tests that examine how people use a design.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Turn interviews, surveys, usability notes, and customer feedback into shared themes, user groups, and prioritized recommendations. Findings include supporting quotes and participant counts, helping teams connect research evidence to concrete product improvements.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Analyze product usage in PostHog and manage experiments, dashboards, surveys, and feature flags, which control feature availability. Use connected tools to investigate user behavior and errors, run queries, and summarize findings with numbers and links.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Design studies that combine quantitative data, such as surveys, with qualitative evidence, such as interviews. It recommends a suitable design and outlines study phases, participant selection, timing, and ways to combine findings into an integrated interpretation.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Clean survey datasets using their codebooks, which explain variables and response codes. Check missing values and outliers, harmonize variables across years, and prepare combined data with a cleaning report, variable definitions, and recorded transformation history.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Analyze interviews, focus groups, and open-ended survey responses using Braun and Clarke's six-phase framework. Label meaningful passages, develop and review themes, and produce an academic Word report with an annotated map showing theme relationships.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Design a 360-degree feedback survey or write a structured 360 feedback report. Use when asked to build a 360 feedback process, write 360 feedback for a colleague, design a feedback survey, or produce a feedback report. Produces either a complete survey instrument with rating scales and open-ended questions, or a structured narrative feedback report with themes, strengths, and development areas.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Market sizing and market structure work — TAM/SAM/SOM built top-down and bottom-up then reconciled, segmentation, demand triangulation, and survey design. Use when sizing a market, writing a sizing memo, or fielding a survey.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create original surveys, benchmarks, and aggregated data nobody else has. Automate data collection for content moats. Triggers on: "create original data", "proprietary data", "survey design", "benchmark study", "original research", "data-driven content", "create a survey", "industry benchmark", "aggregated data", "unique data", "first-party data", "data moat", "generate research data", "create a study", "original statistics", "data nobody else has", "competitive data advantage".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Launch and continue the Volcengine AI Research survey workflow for concept testing, audience design, questionnaire drafting, interview guide generation, execution confirmation, progress checks, and result queries. Use this skill when the user wants to create, revise, confirm, execute, or follow up on a real AI research survey task in ABCompass instead of doing generic brainstorming, copywriting, translation, summarization, or broad market discussion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Diagnoses product-market fit from survey, usage and pipeline data and returns a scored verdict with the next moves. Use when you ask 'do we have product-market fit', 'is our PMF survey good enough', 'what does 35% very disappointed mean', 'should we scale yet', 'why is growth stalling', or need a Sean Ellis survey, retention check, or PMF level read. Draws on 137 insights from 66 Lenny's Podcast guests incl. Sean Ellis, Todd Jackson and Rahul Vohra.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Survey the codebase for analogous features, reusable utilities, and existing patterns relevant to a proposed change, reading any source the task names outside this repo. Returns structured findings without writing code. Use when the user asks to "survey patterns", "find existing patterns", "look for analogous features", "check how similar things are done", "find prior art for this change", or needs pattern context before planning a change.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user wants a comprehensive literature survey on a specific research topic. Outputs a complete PDF survey (6–20 pages, 60+ real citations, 100+ recommended) with LaTeX source, topic-specific publication figures, and a classified literature table. Single-stage, no Python runtime.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Conducts a systematic related-work / literature-survey / state-of-the-art review for a research question by defining survey dimensions, searching each axis, building a taxonomy of prior work, identifying the gap, and producing a positioning narrative for a paper's Related Work section. Goes beyond a flat paper list to deliver structured analysis. Use when the user is starting a new research project and needs to map the landscape, asks "what's been done on X?" or "how does my idea compare to existing work?", needs to write or revise a Related Work / Background / Prior Art section, wants to identify a research gap or position their contribution, or asks to build a taxonomy of approaches in a research area.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Designs survey instruments: question wording, scales and index reliability, flow and treatment placement, pretesting, attention and speeding rules, and sensitive questions. Use when writing or revising survey questions, choosing scales, ordering blocks, or planning a pilot.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.