Signal Room: Interview Synthesis
Turn interview transcripts into evidence-backed insight
Description
Recommended by
nene@YouMind
Why we love this skill
An editor’s pick for rigorous, decision-ready interview synthesis. It keeps every insight tethered to verbatim evidence, separates behavior from belief and wish, surfaces disconfirming evidence and disagreement, and makes sample limits, confidence, and next research unmistakably clear.
YouMind already transcribes your calls, interviews and podcasts. Signal Room is what happens next. Drop in one transcript or twenty and get back a research synthesis an actual analyst would sign: coded themes, verbatim evidence with timestamps, the places people disagree, and a ranked answer to the decision you are trying to make. The method is real qualitative practice, not summarisation: • Open coding that works quote-first — no quote, no code — with codes named in the participant's own words rather than analyst jargon • Every code tagged Behaviour, Belief or Wish, because "I would definitely pay for that" is not the same class of evidence as "I paid for that last month" • Themes stated as falsifiable sentences, with strength counted in participants rather than quotes, and disconfirming evidence hunted for on purpose • A tension map showing where your participants genuinely split and what predicts which side they fall on • An opportunity backlog written as "when [situation], [who] wants [outcome] because [reason]", each rated Strong, Suggestive or Anecdotal • A direct answer to your decision question, with a stated confidence level and what would change it • The three questions this round could not answer, and who to interview next Guardrails that matter: it never invents or polishes a quote, it refuses to report percentages on fewer than twelve participants, it pseudonymises participants by default, and it will tell you to your face when n=1 means you have a hypothesis rather than a finding. For product managers, UX and market researchers, journalists, consultants, founders doing customer discovery, and anyone sitting on hours of recordings and no findings.
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Signal Room: Interview Synthesis
Turn interview transcripts into evidence-backed insight
Description
Recommended by
nene@YouMind
Why we love this skill
An editor’s pick for rigorous, decision-ready interview synthesis. It keeps every insight tethered to verbatim evidence, separates behavior from belief and wish, surfaces disconfirming evidence and disagreement, and makes sample limits, confidence, and next research unmistakably clear.
YouMind already transcribes your calls, interviews and podcasts. Signal Room is what happens next. Drop in one transcript or twenty and get back a research synthesis an actual analyst would sign: coded themes, verbatim evidence with timestamps, the places people disagree, and a ranked answer to the decision you are trying to make. The method is real qualitative practice, not summarisation: • Open coding that works quote-first — no quote, no code — with codes named in the participant's own words rather than analyst jargon • Every code tagged Behaviour, Belief or Wish, because "I would definitely pay for that" is not the same class of evidence as "I paid for that last month" • Themes stated as falsifiable sentences, with strength counted in participants rather than quotes, and disconfirming evidence hunted for on purpose • A tension map showing where your participants genuinely split and what predicts which side they fall on • An opportunity backlog written as "when [situation], [who] wants [outcome] because [reason]", each rated Strong, Suggestive or Anecdotal • A direct answer to your decision question, with a stated confidence level and what would change it • The three questions this round could not answer, and who to interview next Guardrails that matter: it never invents or polishes a quote, it refuses to report percentages on fewer than twelve participants, it pseudonymises participants by default, and it will tell you to your face when n=1 means you have a hypothesis rather than a finding. For product managers, UX and market researchers, journalists, consultants, founders doing customer discovery, and anyone sitting on hours of recordings and no findings.
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Helps product managers, founders, and app developers understand AI papers through historical causal links, turning those insights into product judgments, technical boundaries, engineering intuition, and opportunity analysis.
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Your all-around movie buddy—worth using for any movie. Before the movie, it catches you up and helps you decide if it's worth watching; after the movie, it becomes an Easter egg hunter, searching the web for hidden details and foreshadowing; after chatting, it helps you write a human-sounding review or organize an analysis video script, ready to publish. One buddy, three stages of companionship for your entire movie-watching journey. 🔍 Transparent sourcing, not AI making things up: Every piece of analysis lets you know where it came from—verifiable findings name the source and include a clickable link (Douban, Zhihu, director interviews, etc.). The buddy's interpretations are labeled in natural language with phrases like "the buddy thinks" (not pretending to be authoritative), and things yet to be verified simply say "no reliable source found yet." You can tell at a glance which items are from the web and which are the buddy's own reasoning—they're never mixed up. Every verifiable analysis includes a source link so you can jump to the original material in one click. 📚 Pre-movie catch-up: fast, accurate, and spoiler-free. No time to watch the previous installments before a sequel? Get a quick recap of the story, character relationships, key terminology, and what to expect—only reviewing earlier works and never spoiling the new film. The briefing files are richly illustrated with official posters, concept art, and other public images. There's also an "Is it worth watching?" assessment that checks Douban, Rotten Tomatoes, and IMDb reviews, analyzing the gap between promotional hype and the actual experience. 🥚 Post-movie Easter egg hunter for satisfying deep dives. After the movie, if you're left wondering "What did that detail mean?" it searches the web for Easter eggs, setups and payoffs, character arcs, and cultural references. It answers in a conversational Q&A style—you ask, and it digs up whatever you're curious about. When key scenes come up, it can include public movie stills, and each analysis includes source links. 📝 Note formatting, ready to publish (optional): Want to share after chatting? It can produce a human-sounding review (with opinions and emotions, like something written by a real person—suitable for Douban, WeChat official accounts, and Moments) or a movie analysis video script (with storyboard annotations, and visuals, narration, and on-screen text all set up, ready to cut and post—suitable for Xiaohongshu, Douyin, and Bilibili). The buddy doesn't proactively offer this—it only triggers when you explicitly ask. 🎬 Covers most movies, animation, and TV series. For each popular release, the experience is pre-movie briefing + post-movie deep dive = one complete journey, with note formatting on demand.
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Provide a book title (and optionally your occupation, position, or identity). Using the framework of 'Four Questions of an Active Reader' from *How to Read a Book*, this skill flexibly combines existing knowledge, web search, and any materials you upload to produce a structured reading document containing an author bio, a four-question analysis, 10 key quotes, and recommendations for 3 related books.
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