'synthesis' 검색 결과

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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VS-Enhanced Literature Review Strategist - Comprehensive support for multiple review methodologies Full VS 5-Phase process: Prevents Mode Collapse and presents creative search strategies Supports: Systematic Review (PRISMA 2020), Scoping Review (JBI/PRISMA-ScR), Meta-Synthesis, Realist Synthesis, Narrative Review, Rapid Review Use when: conducting any type of literature review, systematic reviews, meta-analyses, scoping reviews, finding prior research Triggers: literature review, PRISMA, systematic review, scoping review, meta-synthesis, realist synthesis, narrative review, rapid review

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Synthesises a batch of customer feedback (survey answers, reviews, ticket and chat comments) into a DRAFT themed report: coded themes with record counts and shares, anonymised verbatim quotes cited to record codes, contradictions and unverified claims, and the follow-up questions to answer next. Produces no sentiment score or percentage positive as fact; ratings appear only as distributions with n. Use when the user asks to "theme this feedback", "what are customers saying", "summarise these survey answers", "analyse these reviews", "find the top complaints in these comments" or "code this voice of the customer data". Do not use for exit interviews, use exit-interview-synthesis instead; for sorting a live queue and drafting replies, use ticket-triage-pack; for project retrospectives, use lessons-learned-synthesis. Drafts for human review; never approves, authorises or signs off.

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Prepare experiments for Ginkgo Cloud Lab by choosing a protocol, organizing required inputs, checking configured pricing, and navigating browser ordering. Covers protein expression, RNA synthesis, stability assays, and setup of measurement methods.

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• Choosing a protein expression and purification protocol
• Preparing inputs for mRNA or circRNA synthesis
• Reviewing stability assays and measurement method setup

Guide a product team from a problem hypothesis through customer interviews, research synthesis, and solution experiments. Use six structured phases to gather evidence, compare options, and decide whether to build, change direction, or stop.

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• Validating customer problems before development
• Investigating onboarding drop-off or churn
• Organizing interviews and research synthesis

Find recurring concept combinations across the wiki that lack an explicit synthesis page, then create cross-cutting synthesis pages. Use for knowledge synthesis after the vault has accumulated enough material.

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Collecting and synthesizing user feedback across channels (support tickets, NPS, in-app feedback, sales calls, social mentions, customer councils) into a continuous signal that informs product decisions. The triage discipline that distinguishes loudest-voice (whoever complains most wins) from averaged-noise (every signal weighted equally) from triaged-synthesis (signal weighted by source quality, frequency, and decision relevance). Triggers on user feedback, customer feedback aggregation, NPS, support ticket analysis, customer councils, feedback synthesis, voice of customer, feedback triage, in-app feedback. Also triggers when feedback channels overflow with volume that does not produce decisions, when the loudest-voice problem is steering roadmap, or when continuous feedback streams need synthesis discipline.

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Synthesise completed KUD charts into a developmental progression matrix and per-competency narrative sections. Use when you need a programme-level view of how knowledge, understanding, and performance develop across bands.

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Comprehensive patterns for AI-powered audio generation including text-to-music, voice synthesis, text-to-speech, sound effects, and audio manipulation using MusicGen, Bark, ElevenLabs, and more. Use when "music generation, text to music, AI music, voice cloning, text to speech, TTS API, ElevenLabs, MusicGen, Bark, audio synthesis, sound effects generation, voice synthesis, AudioCraft, " mentioned.

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Synthesise completed KUD charts into a developmental progression matrix and per-competency narrative sections. Use when you need a programme-level view of how knowledge, understanding, and performance develop across bands.

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Synthesises retrospective notes, closing reports and post-implementation reviews into a DRAFT lessons-learned document: themed lessons with source counts, anonymised quoted evidence graded by strength, repeats against a prior register, contradictions, and a recommended owner with a stated basis for each follow-up. Names no individual or vendor and assigns no blame. Use when the user asks to "compile the lessons learned", "write up the retrospective", "theme the close-out notes", "what did we learn across these projects" or "refresh the lessons register". Do not use for a single sprint's review, use sprint-review-summary instead; for an incident investigation, use incident-postmortem-drafter; for customer feedback themes, use customer-feedback-theme-synthesis. Drafts for human review; never approves, authorises or signs off.

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Synthesises exit interview notes or leaver survey responses into a DRAFT themed report: coded themes with record counts and shares, anonymised verbatim evidence, breakdowns by broad group only for groups that meet a minimum group size, referred items and open questions for the people team, without naming or identifying any individual. Use when the user asks to analyse, summarise, code, theme or report on exit interviews, leaver feedback, attrition interviews or departure surveys, or says "what are our leavers telling us", "theme these exit interviews" or "summarise the leaver survey". Do not use for customer or product feedback, use customer-feedback-theme-synthesis instead; for redacting one document with no theming, use document-deidentification-pass. Drafts for human review; never approves, authorises or signs off.

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Synthesises training survey responses and manager notes into a DRAFT training needs report by role: coded needs with record counts per role (n of N), the evidence type behind each count, anonymised quotes cited to record codes, disagreements between what staff report and what managers observe, gaps where a role is under-represented or a required skill has no evidence, and follow-up questions to settle before any course is designed. Never rates an individual, ranks a team or turns a count into a competence verdict. Use when the user asks to "analyse this training survey", "what training do our teams need", "summarise the manager feedback on skills gaps", "build a training needs analysis by role" or "which roles have the biggest skill gaps". Do not use for turning an agreed need into a course, use course-outline-builder instead; for exit interviews, use exit-interview-synthesis. Drafts for human review; never approves, authorises or signs off.

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Build kokoro-js-jp and run its real-browser e2e suite (Worker + WASM openjtalkjs g2p + ONNX kokoro-js synthesis, English and Japanese). Use when asked to verify this package actually works in a browser, to check whether a change broke synthesis, or to add browser-level regression coverage for a bug in the g2p/synthesis pipeline that vitest's pure-function tests can't catch. Not for typecheck/lint/unit-test requests — use npm run typecheck / npm test for those.

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여러 차례 인터뷰로 브랜드의 목적, 고객상, 개성과 말투를 정리합니다. 창업자들의 공통점과 인식 차이도 살펴 협업자에게 공유할 브랜드북으로 만듭니다.

• 새 브랜드의 방향 설정
• 기존 브랜드의 포지셔닝 재검토
• 여러 창업자의 인식 조율

여러 차례의 대화로 브랜드의 목적, 고객상, 말투를 구체화합니다. 답변과 진행 상황을 저장하고 브랜드북으로 정리해 창업자의 생각을 제작 담당자와 공유하도록 돕습니다.

• 새 브랜드의 방향을 정합니다
• 기존 브랜드의 포지셔닝을 재검토합니다
• 디자이너와 작가에게 전달할 자료를 만듭니다

Turn research findings stored in memory into structured reports with evidence ratings, source references, and practical recommendations. Compare conflicting claims, identify unresolved questions, and explain limitations so accumulated research can support decisions and next steps.

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• Combine findings from several research sessions
• Compare conflicting claims and their supporting evidence
• Prepare a research brief with recommended next steps

Delegate complex work through a tree of Claude Code sub-agents. Each level uses its own working context and returns concise summaries, helping the coordinating agent manage research, verification, and synthesis without retaining every intermediate detail.

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• Divide research, expansion, verification, and synthesis into layers
• Handle work with more intermediate detail than one agent can retain
• Assign specialized checks to different leaf agents

Design multi-agent workflows for research, reviews, and migrations. Organize work across different evidence sources, add independent checks, and combine findings while preserving source references, unresolved questions, and limits on what was examined.

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• Plan research across multiple evidence sources
• Review implementation and tests from different angles
• Compare candidate solutions with independent judges

Develop a research question, search and verify literature, and combine findings into an academic report. Modes also support guided research discussions, claim checking, paper comparisons, and systematic reviews with optional meta-analysis, which statistically combines study results.

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• Clarify a research direction through guided questions
• Search literature and compare findings across sources
• Check specific claims against supporting sources

Researches external facts with available web tools and prioritizes original sources. Produces a linked synthesis that checks dates and versions, separates facts from inference, and identifies questions the available evidence has not resolved.

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• Checking release notes for recent changes
• Researching official documentation for a specific version
• Investigating earlier work and related approaches

Plan voice AI systems by comparing direct speech processing with separate transcription, language generation, and speech synthesis stages. Covers response delays, detecting when people speak, interruptions, and noise handling to guide conversational interface design.

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• Compare architectures for a voice AI system
• Review delays across conversation processing stages
• Design handling for interruptions during speech

Research a topic from multiple angles, preserve sources according to your privacy preferences, and summarize each one. Combine the evidence into a self-contained reference page, including limitations and counterarguments, with options to deepen the research later.

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• Building a reference guide on a new topic
• Keeping sources alongside individual summaries
• Comparing evidence, counterarguments, and limitations

Turn selected research conversations or notes into themes supported by evidence and counterexamples. Distinguish observed behavior from preferences and hypotheses, assess confidence, and suggest a small next experiment with an observable measure of success.

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• Finding recurring themes across research interviews
• Comparing evidence, counterexamples, and confidence
• Planning a small experiment to test findings