「survey」の検索結果

Use when analyzing the material of an Accounting, Organizations and Society (AOS) manuscript — coding and interpreting qualitative field data, estimating experimental and survey models, or running theory-laden archival analyses, with an audit trail appropriate to each tradition. Analyzes and reports; it does not design the study (aos-methods).

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Use when designing the study for an Accounting, Organizations and Society (AOS) manuscript — qualitative field studies (access, case logic, interviews, observation), behavioral experiments, surveys, historical/archival inquiry, or theory-laden archival designs, each with the ethics and site-anonymity groundwork done early. Designs the inquiry; it does not run the coding or estimation (aos-data-analysis).

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Use when the research design and method are the bottleneck for an Academy of Management Journal (AMJ) manuscript — matching design (archival, survey, experiment, multi-method, field) and level of analysis to the theoretical question. Designs the study; it does not run the estimation or validity checks (amj-data-analysis).

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Aggregate customer feedback from multiple sources — support tickets, NPS comments, Slack messages, G2 reviews, call transcripts, survey responses — into a unified VoC report with theme clustering, sentiment analysis, trend detection, and actionable recommendations for product, marketing, and CS teams. Chains review-site-scraper for public review data.

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Take raw customer inputs — interview transcripts, survey responses, Slack quotes, support tickets, review excerpts — and generate a structured case study draft with problem/solution/result narrative, pull-quotes, metric callouts, and multi-format outputs (full case study, one-pager, social proof snippet, sales deck slide). Pure reasoning skill. Use when a product marketing team has customer signal but no time to write the story.

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Watch a brand's own product footage (screen recording, product film), pick the moment that proves each line with the user, and render those picks as a product layer — free, local. survey.py turns footage into timestamped contact sheets + scene cuts + motion so the agent can actually look at it; the agent writes a cut list (beat → source window + framing); preview.py draws it as a review sheet the user corrects round by round; cut.py renders the approved list into a silent 1080x1920 layer with the creator's area left as a plate. Also frames footage as a filmed screen (keystone, bezel, handheld drift) with dissolves between beats, and takes still screenshots as sources. Use for any format that shows real product footage beside, between or instead of a creator (split-screen, screen inserts, walkthroughs).

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Turning research artifacts into actionable PM insight. Customer interviews, user research notes, support ticket reviews, sales call transcripts, survey data, in-app feedback, all synthesized into the decisions they are meant to inform. The discipline of moving from raw discovery data to clear product direction without losing signal in the synthesis or fabricating insight that was not actually there. Triggers on research synthesis, customer interview synthesis, user research analysis, discovery readout, research insights, sales call analysis, support ticket analysis, qualitative data analysis. Also triggers when a team has done research but cannot turn it into decisions, when synthesis is producing pretty decks but no roadmap movement, or when an upcoming PM decision needs to be grounded in research already conducted.

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Synthesize raw user research (interviews, surveys, tickets) into themed findings and decision-ready briefs. Use when synthesizing user interviews, building a findings brief, or communicating research to stakeholders.

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People analytics across workforce metrics, predictive modeling, and employee insights. Use when building turnover models, analyzing engagement surveys, running pay equity regressions, or scoring flight risk.

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SaaS churn reduction covering cancel flow design, dynamic save offers, exit survey architecture, dunning sequences, payment recovery, win-back campaigns, and churn impact modeling.

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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.

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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.

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Research a US employment law topic across federal, state, and city jurisdictions and produce structured research notes with proper source attribution. Use this skill any time the user asks about US employment laws, regulations, or pending legislation - from a single jurisdiction question to a 50-state survey. Triggers include phrases like "research [employment law topic]", "what are the laws on [employment topic]", "state-by-state [employment topic]", "help me understand [topic] across the US", or any prompt that asks for a legal landscape overview before another deliverable. Always run this BEFORE the employment-law-dashboard skill if a dashboard is the eventual output. Output is a structured research note that distinguishes primary sources (statutes, regs, agency guidance) from secondary sources (law firm alerts, tracker orgs).

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Survey the codebase, pick ONE high-leverage deepening opportunity (filtering out anything already proposed), and publish it as a PRD-shaped GitHub issue via /to-prd-project. Designed to run unattended in the daily architecture-review workflow.

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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.

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Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.

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Review open PRs two ways - default is a per-PR deep review with severity-tagged findings, inline comments, and a verdict; --survey runs a risk-tiered triage digest of what's safe to merge first

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Legacy survey-based DESIGN.md writer redirect. Use for old omd:design requests only to route them to the Core v2 Autopilot or init workflow; this compatibility skill never writes DESIGN.md itself.

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Writing self-loop for surveys: run the strict section-quality gate, then rewrite only the failing `sections/*.md` files until the report is PASS.

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Use when a `research-brief` workspace has a small paper set plus outline and needs a compact reader-facing briefing instead of a full survey.

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Polish a single H3 unit file under `sections/` into survey-grade prose (de-template + contrast/eval/limitation), without changing citation keys.

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Define evidence-first table schemas for a survey: what each table must answer, row unit, columns, and which evidence-pack fields are required to fill it.

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Write survey prose into per-section files under `sections/` so each unit can be QA'd independently before merging.

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Run a research Workflow end to end when the user requests a survey, brief, review, tutorial, or idea exploration; route an unbound goal, execute one eligible Unit at a time, and stop at checkpoints or diagnosed failures.

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。