「how」の検索結果

For a repository in the babysitter-users catalog, locate its babysitter processes and any committed runs (.a5c/runs/<runId>/) and perform a retrospective on a chosen run -- what went well, what failed, process suggestions, quality of effect design, breakpoint patterns -- mirroring the /babysitter:retrospect workflow but applied to an external repo. Invoke when asked to "retrospect on repo X's run", "analyze how someone else used babysitter", or "review an external babysitter run".

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演讲与分享教练。基于Patrick Winston（MIT AI教授）的How to Speak方法论，帮助准备线下培训、技术分享、B站教程视频等演讲场景。当用户提到"演讲"、"分享"、"培训"、"讲课"、"PPT演讲"、"开场"、"结尾"、"如何讲"、"演讲结构"时使用此技能。

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Explain any topic, code, concept, or error tailored to a specific audience's level of understanding. Use this skill whenever the user says 'explain like I am', 'ELI5', 'explain this to my', 'break this down for', 'dumb it down', 'simplify this for', or asks you to explain something to a specific person or audience type (e.g., 'explain this to a manager', 'how would I explain this to my mom', 'make this understandable for a 5th grader'). Also trigger when the user mentions wanting to understand something at a particular level, or asks for an explanation targeting a non-technical audience. Even partial matches like 'explain to my wife' or 'tell my boss' should trigger this skill.

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Strip the machine fingerprint out of any draft - em dashes, AI slop words, invisible watermark characters - and score it against a five-check detection panel before it goes out. Use whenever text needs to sound human, when the user says humanize, "does this sound like AI", "remove the em dashes", "de-slop this", "this sounds like ChatGPT", or before any caption, script, comment, reply or DM is shown to the user.

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Score an Instagram profile out of 100 against a 12-part rubric and rewrite the parts that lose points - name field, bio, link, highlights, pinned three, grid. Use when the user says "optimize my profile", "fix my bio", "score my Instagram", "why don't people follow me", or pastes their profile and asks how it reads.

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Write Instagram DMs that get replies - the keyword delivery, the first message to someone who engaged, the collab pitch, and the two follow-ups. Use when the user says "DM this person", "what do I send them", "outreach message", "how do I follow up", "pitch this brand", or is reaching out to someone specific.

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Go and find the reels that are actually working right now in the user's niche, rank them by how far each beat its own account, name the hook formula each one used, and turn that into a swipe file they can shoot from. Use when the user says "find viral videos", "what's working right now", "what are people posting in my niche", "reverse engineer this account", "build me a swipe file", "why is this reel doing numbers", or asks what to make next and has no evidence to answer with.

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Worked full-length scripts of banqiang-system Chinese opera with their creation records (板腔体全本语料库). Primary texts; 翁偶虹《锁麟囊》 (the revised score edition, 65 arias, 15 self-account-vs-score checks), 汪曾祺等《沙家浜》 (the 1965 text, not the 1970 one; 36 arias, a 12-row two-version diff), 田汉《白蛇传》 (the 1955 book, not the web revision; 16 scenes, 王瑶卿说腔五条), 杨兰春《朝阳沟》 (1978 revival, 50 arias, 口语入唱, per-scene sung/spoken ratios), 魏明伦《潘金莲》 (跨时空, missing pages), 罗怀臻's 越剧《李清照》《真假驸马》, 淮剧《金龙与蜉蝣》, 甬剧《典妻》; plus index tables of 翁偶虹's 60 创作记 and 范钧宏's seven 改编札记. Use when you want to see how a 唱工戏 lays out its 板式, need real scene counts, aria counts and 辙口 to imitate, want the road from raw material to 审腔, are writing a 现代戏 or colloquial lyrics, or compare one author across two声腔 systems. Method is in sw-chinese-opera-banqiang; this skill holds the worked scripts and their creation records.

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Playwriting for banqiang-system Chinese opera (板腔体：京剧、豫剧、越剧、秦腔、评剧、沪剧、淮剧、川剧弹戏), where sung passages are paired seven- or ten-character lines varied by metre (板式) rather than filled into fixed tune patterns. Covers genre (唱工戏／做工戏／武戏), the main line, technical structure and 排场, how 行当 and a named star decide the writing, 程式, lyric craft (唱词：上下句、重点句、垛句、辙口), 宾白 and the sung/spoken seam, duets, what the writer marks on the page (Peking-opera vs Yue-opera style), the interface with actors and musicians, restoring old plays, and three contemporary routes including 现代戏. Sources; 范钧宏、翁偶虹、刘吉典、樊尚林、张庚郭汉城、罗怀臻、陆军, plus full scripts (锁麟囊／沙家浜／白蛇传／朝阳沟／潘金莲). Use when writing or revising 唱词, choosing 板式, writing for a performer or role-type, adapting a traditional play, writing a 现代戏, judging a project's genre, marking 锣鼓, or drawing the boundary before general dramaturgy skills apply. Not for 元杂剧/传奇/昆曲, which are the qupai system; see sw-chinese-opera-qupai.

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Case studies of television series writing (剧集案例库) from primary texts; Sorkin's six West Wing teleplays (act-page tables, eight act-out types); Chase's five Sopranos scripts (the 35-beat A/B/C/D recipe, what a pilot refuses to explain); Fellowes's annotated Downton Abbey season two (19 storylines, 419 footnotes); Waller-Bridge's Fleabag Scriptures (the six-episode half-hour template); Calvisi's eight minute-by-minute pilot beat sheets (Breaking Bad, Mad Men, Game of Thrones and more); Landau's 47-series structure appendix; Miller's Hannibal and HTGAWM breakdowns; Goldberg & Rabkin's beat sheets; Sakamoto Yuji's We Made a Beautiful Bouquet (a feature) and Noh Hee-kyung's The Most Beautiful Goodbye. Use when you want a worked example of how an episode or pilot is built, need real act lengths, scene counts or storyline grids to imitate, are breaking a multi-thread ensemble episode, designing a bottle episode or a finale, writing a relationship or family drama, or ask 某一集是怎么写的 / 这部剧的结构表.

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Writing a Succession-style ensemble series (继承之战群像剧写法) — distilled from Jesse Armstrong's complete shooting scripts for all four seasons, 39 episodes (Faber 2023), with his introductions and footnotes, plus Frank Rich's and Lucy Prebble's essays on the writers' room. Covers the invisible-act three-test for scripts with no ACT marks, container episodes built on a ceremony's running order, pressure chambers, one core question per episode, finales with fewer and longer scenes, the absent protagonist at the climax, humiliation passed downward, stage directions carrying subtext and "maybe", reversals turned on one word, writing long, alts, the mega-chart, and engineering an ending once the plot engine loses pressure. Use when the user wants a dynastic family drama, a media-power ensemble, a wedding/funeral/summit set piece, a streaming hour with no act breaks, a finale that redraws alliances, or asks how to "Succession-ize" a script or kill a lead mid-season.

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Worked qupai-system (曲牌体) opera scripts, act by act. Guan Hanqing's three surviving zaju (窦娥冤／救风尘／金线池 — twelve acts, 126 tunes, one mode and one rhyme per act, sung/spoken ratios); Tang Xianzu's 牡丹亭 (55 scenes, ~420 tunes, 集唐 closing quatrains, the 圆驾 south-north composite suite); Kong Shangren's 桃花扇 (44 scenes plus four unnumbered, the 副末 frame line, upper/lower halves, a fan's seven transformations, his sixteen 凡例); 长生殿 (Wang Jilie's fifty-scene staging table); Wei Minglun's 巴山秀才 (1983 Sichuan 高腔, 43 tunes, nine 帮腔 passages). Every case states its edition and collation status, then structure, tunes, stage conventions and transferable devices. Method is in sw-chinese-opera-qupai; this skill holds the worked scripts. Use when you want a real example of how a 传奇 or 杂剧 is assembled, need actual scene counts and tune counts to imitate, are judging where a famous script breaks prosody, or need models for 副末开场, 集唐下场诗, 南北合套 or 帮腔 (曲牌体全本／牡丹亭／桃花扇／窦娥冤／救风尘／长生殿／巴山秀才／唱段表／结构表).

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Case studies of American screenwriting (美国电影剧作案例) — Mei Feng's readings of the Hollywood Western (value pairs, four oppositions), screwball comedy (strong heroine, buddy vs adversary two-hander), Billy Wilder (disguise, Lubitsch touch, meet-cute), Hitchcock and his writers, Adaptation, Mildred Pierce (eight drafts, woman's film + noir), Thelma & Louise ("but" method, mirror pair), Fargo (Coen method), Good Will Hunting (five-part structure), American Beauty (POV strategy, genre mix), Eternal Sunshine (1:5:1, image motifs); Walter's American Graffiti; the Hollywood masterclass films (Bourne, Guardians, Zootopia, Thor); Hoxter's Winter's Bone and Jojo Rabbit; Snyder's Miss Congeniality; Field's Chinatown. Use when you want a worked example of how a specific American film's script is built, when analysing a film for structure, character or theme, or when looking for a model to imitate for a Western, screwball, noir, buddy, coming-of-age, black comedy or non-linear romance.

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Smallest personal narrated-explainer-video pipeline (spoken narration over visuals, not an audio podcast), fully tool-agnostic and autonomous by default — topic → research ∥ asset collection → script → TTS → video → 4K render ∥ publish info + cover. The skill defines the pipeline logic and self-verified checkpoints; any TTS backend and any video tool (Remotion, HyperFrames, CapCut, ...) work, and how much human oversight to apply is set by the working project's AGENTS.md/CLAUDE.md, not here. Use when the user wants a quick personal narrated video with minimal steps, whether or not they name the tool stack. Do NOT trigger for audio-only podcasts, written episodic content, or heavy multi-format production.

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Assesses whether and how an existing mobile product should migrate to React Native. Use when auditing one or more product repositories for migration readiness, including products whose iOS, Android, and other clients live in separate directories or repositories; choosing brownfield, greenfield, or a checkpoint-based path; defining a representative trial; or preparing a baseline and ROI decision before implementation. When product scope or material evidence is unavailable, grills the stakeholder with exactly one question per turn instead of sending a questionnaire.

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House style for user-facing documentation — voice, scope, structure, and what to leave out. Use this skill whenever writing, editing, or reviewing anything a user reads to learn how to use a tool — help center articles, getting-started guides, tutorials, feature docs, README usage sections, in-app help, release notes, or FAQ entries. Trigger it even when the request is phrased plainly — "document this feature", "write docs for X", "explain this to users", "write a README for this library", "turn these notes into a guide" — and even when no style guidelines are mentioned. Also use it to review existing docs for tone, bloat, or leaked implementation detail. Do not use it for internal engineering docs, architecture write-ups, RFCs, or code comments.

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Extract a written voice profile from your own prior papers, then use it to keep new drafts sounding like you. Reads a corpus one document at a time via subagents, produces a reusable profile on disk (lexicon, sentence rhythm, how you open and close, hedging habits, deliberate quirks), and audits a draft against it. Use when the user says "make this sound like me", "match my voice", "profile my writing", "why does this draft not sound like my papers", or before drafting prose that will carry their name. The positive counterpart to /humanize, which only detects AI tells.

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Stress-test a finding against the choices you did not make. Enumerates the discrete forks a competent analyst could have taken (measure definition, sample filter, control set, clustering level, weighting, functional form), runs the specification grid, and reports the distribution rather than a point estimate — then attacks the identifying assumption with named, computable sensitivity statistics. Use when the user says "is this robust", "challenge this result", "specification curve", "multiverse", "how sensitive is this", "what if I'd used a different measure", "stress-test my estimate", or before a result becomes a headline claim. NOT a reviewer of prose or code — it challenges the CLAIM.

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Keeps a project's to-do list and memory in GitHub issues — files each finding (from a review, an audit, or the user) as its own issue without duplicates, lists the open issues that bear on the current work, and closes an issue with a comment recording what was wrong, what was tried, what worked, and how it was fixed. Use when review findings or a list of problems should become tracked work (a paper's misleading claims, a codebase's bugs, improvements for later), when starting or resuming work and deciding what to do next, or when a fix has landed and its issue should be closed with a record. Needs the GitHub CLI; warns before posting to a public repository.

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Compute statistical power, required sample size, and minimum detectable effect (MDE) for a study design, then write a registry-ready power section. Handles two-arm RCTs (with clustering / ICC and unequal allocation), multiple-arm corrections, and a simulation-based power option for non-standard designs (DiD/event-study, IV, panel). Use when user says "power analysis", "power calculation", "MDE", "minimum detectable effect", "how big a sample do I need", "is my study powered", "power for an RCT", or when /preregister needs a power section for an experiment. Produces a power/MDE table, power curves, and a methods paragraph to paste into a preregistration.

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Generate a co-author / collaborator handoff brief for a multi-author, multi-machine project — summarizing what changed since the last brief (git delta), the current state of each artifact (manuscript, analysis, slides), open questions, how to reproduce locally, and any restricted-data access steps. Use when user says "coauthor brief", "handoff brief", "bring my coauthor up to speed", "what changed since last week", "onboard a collaborator", "write a handoff for [name]", or before sending a co-author the repo. NOT a commit or a checkpoint — it is the cross-machine, cross-person summary `meta-governance.md` only partially covers.

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dontbesilent 短视频开头优化。诊断开头问题 + 生成优化方案。 触发方式：/dbs-hook、/hook、「帮我优化开头」「开头怎么写」 Short video opening optimization with diagnosis and solutions. Trigger: /dbs-hook, "optimize my opening", "how to write opening"

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Motion-first AI video director for topic-to-video creation. Use when the user gives a theme, idea, article, script, or brief and wants AI to freely create a real animated video instead of a PPT/slideshow-style explainer; when deciding visual metaphors, motion grammar, scene beats, component choices, generated image needs, HyperFrames/Remotion implementation strategy, and anti-PPT QC.

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AI DevKit · Check local AI DevKit readiness and run setup only when status shows onboarding or harness integration gaps.

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