「angle」の検索結果

Use when the user has 2+ video / audio recordings of the same event captured by different devices (cameras, phones, separate audio recorders) and wants them aligned to a single common timeline. Outputs only a lightweight `.sync.json` sidecar per input — original files are never re-encoded. Triggers — "多机位同步", "对齐这几个机位", "match camera timelines", "sync these angles", "audio drift between cameras", "separate audio recorder", "Riverside / Zoom recording that needs to line up".

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。

Use when the user wants to post a daily X/Twitter tweet inspired by one of their recently-published 微信公众号 articles. Picks the newest article that hasn't been tweeted yet, drafts 3 tweet candidates from it (different angles — quote / metaphor / one-liner), posts the chosen one via xurl, records to history. Triggers — "每天发一个 tweet", "从文章里发推", "今天的 tweet", "/wjs-tweeting-from-articles".

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。

Use when 王建硕 wants to systematically improve his X (Twitter) content by iterating on the content-generation prompt (prompts/x/prompt.md, used by the every-6h tweet Action) and finding which prompt version produces the highest-reach tweets. Each prompt edit is a git-SHA-versioned, numbered experiment with a hypothesis; tweets are attributed to the version live at post time and judged on median impressions per tweet. Also mines per-tweet impression data for content-feature signals (angle / length / topic) that feed the next prompt edit. North-star = impressions per tweet. Triggers — "改 X 的 prompt", "X 内容改进", "哪版 prompt 最好", "什么内容 impression 高", "improve my tweets", "A/B test the X prompt", "/wjs-x-improving-content".

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。

Use when the user has 2+ recordings of the same event (each with a `.sync.json` sidecar from wjs-syncing-multicam) and wants them combined into a single MP4 — auto-switching between cams second-by-second on audio energy, with optional picture-in-picture inset. Triggers — "auto-edit multicam", "做个剪辑", "切几个机位", "把这几个视频合成一个", "combine these angles", "PiP overlay".

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。

Generate a weekly X (Twitter) content plan from a theme, audience, and content pillars. Produces per-day recommendations (single tweet vs thread, X hook formula, angle, posting time, primary goal), a single-to-thread mix, daily reply and quote-tweet targets, and a goal-mix balance check across replies, reposts, likes, and bookmarks. Use when the user wants to plan a week of X content instead of ad-hoc posting. Not for drafting one tweet (use x-post-writer) or one thread (use x-thread-builder).

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Turns open-ended requests into things to think WITH instead of answers to accept. Audits the hidden assumptions inside a topic, inverts them into sharp "what if" provocations, branches each one outward, and delivers a fully-expanded mind map image plus the written wonderings. Fire this when the person signals they want to open up a space and think alongside you — "wonder about X", "what are the weird angles on X", "help me think about what this could be", "I want to explore, not decide yet" — or when they invoke /wonder or /wonderpill. Do NOT fire when the same topic is attached to a request for concrete, usable, or decided output: a named deliverable, a count ("give me 5 names"), a deadline ("ideas I can ship this week"), or a "which / what should I pick" question — those want straight answers, not a wonder pill. When it is genuinely unclear which they want, this skill opens by asking one line rather than branching. Not for factual lookups or executing a plan already chosen.

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。

Turns open-ended requests into things to think WITH instead of answers to accept. Audits the hidden assumptions inside a topic, inverts them into sharp "what if" provocations, branches each one outward, and delivers a mind map plus written wonderings. Portable version, no vendor-specific tools required, works on any conversational assistant. Fire this when the person signals they want to open up a space and think alongside the assistant: "wonder about X", "what are the weird angles on X", "help me think about what this could be", "I want to explore, not decide yet". Do NOT fire when the same topic is attached to a request for concrete, usable, or decided output: a named deliverable, a count ("give me 5 names"), a deadline, or a "which / what should I pick" question. When it is genuinely unclear which they want, this skill opens by asking one line rather than branching. Not for factual lookups or executing a plan already chosen.

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。

Suede Labs skill that prepares a song for sync pitching: scene and emotional angles, a supervisor-facing one-sheet, an exists/missing/unknown asset checklist covering master, instrumental, clean, and stems, screened lyric flags, mood tags, and the open clearance questions kept in their own labeled pile. Use when a track is headed for film, TV, ads, games, trailers, or creator campaigns; when a music supervisor, sync agent, or brand asks what a song is and whether it can be used; or when someone asks for a one-sheet, pitch email, or sync package for a release. Prepares review-ready materials only: never claims clearance, promises placement, or sends outreach. NOT FOR: finding and organizing the rights gaps behind an open clearance question (use suede-rights-audit); building the rights transfer package (use suede-rights-passport); linting the release folder itself (use suede-release-linter); a full rollout campaign (use suede-campaign-in-a-box).

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。

Suede-owned earned-media discipline. Use when building a media list, validating a story angle, drafting a journalist pitch, preparing a press kit, evaluating newsjacking, or answering a reporter request. NOT FOR: directory submissions (use suede-directory-submissions), launch packaging (use suede-launch-packaging), social publishing (use suede-social), or contacting anyone without approval.

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。

Produce an intensive, cited analytical report: executive summary, multi-angle findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.

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。

Create and render OpenSCAD 3D models. Generate preview images from multiple angles, extract customizable parameters, validate syntax, and export STL files for 3D printing.

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。

Relationship-first networking skill for identifying the right people to connect with and drafting value-add outreach — not sales, not referral asks. Use when building a network for a job search, career pivot, partnership, or industry access. Covers target identification by purpose, deep LinkedIn + web research on a specific person, brainstorming 10 value-add angles, and drafting three outreach formats: cold networking email (max 200 words), LinkedIn connection request (max 300 characters), and hiring manager follow-up email (120–160 words). Never drafts generic openers or referral asks — always leads with a specific observation and genuine value.

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。

Unified image-generation engine for the product-shots ecosystem. Dispatches to the right model family (OpenAI gpt-image-2 / Gemini gemini-3-pro-image-preview Nano Banana Pro) with one parameterised script for text-to-image and image-to-image. Primary backend: OmniMaaS / Cloubic gateway (https://api.omnimaas.com/v1); also supports any OpenAI-SDK-compatible gateway via fallback env vars. Auto-resizes oversized reference images to prevent edge-proxy timeouts. Use when the user says "generate an image", "make a picture", "create a visual", "render this", "edit this image", "做一张图", "生成图片", "改这张图" — or when invoked as the image-generation backend by another product-shots skill (main-image / detail-page / ad-creative / social-post / multi-angle). NOT a creative-direction skill: takes a prompt + optional reference images, returns a file path.

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。

Front-door router for the product-shots ecosystem. Clarifies underspecified visual creation requests through a 4-stage state machine, injects platform visual DNA (Amazon + 7 social platforms) and industry visual DNA (7 industries), enforces a unified Negative Constraints prompt patch, then routes to one of five downstream business skills (product-shots-main-image / product-shots-detail-page / product-shots-multi-angle / product-shots-ad-creative / product-shots-social-post). Use when the user says "I need a product image", "design something for my listing", "I need content for Instagram", "make an ad for me", "make a cover image", "create a post", "做一个商品图", "帮我做个详情页", "帮我做个广告图", "做一个社媒图", "做一张图", "帮我设计", "做个封面" — i.e. any underspecified visual creation request that needs clarification before generation. This is the intent-routing hub of the product-shots ecosystem.

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。

Designs Amazon-compliant main product images and the 7 secondary image types (Infographic / Multi-angle / Detail Shot / Lifestyle / Variants / What's in Box / Size Reference) — with platform-mandatory main-image rules, conversion-rate-tuned secondary types per product category, and multi-image consistency anchored to the main image URL. Use when the user says "Amazon main image", "亚马逊主图", "product main image", "white background product image", "Amazon listing image", "亚马逊副图", "secondary images", "product carousel images", or any request for the 1:1 product image suite that lives on the Amazon detail page carousel. For A+ Content / detail-page modules (21:9 Hero Banner and 3:2 module layouts), see the `product-shots-detail-page` skill.

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This skill should be used when the user asks to "research this company", "look into this person", "find the best angle for reaching out to", "who should I contact at [company]", "what does [company] care about", or when preparing outreach to a specific target. Also triggered by "help me prepare for an interview with [company]" or "I want to apply to [company]". Combines lead-generation intelligence with LinkedIn-specific approach planning.

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。

Refactors code while preserving behavior. Use when reducing technical debt, planning codemods, applying strangler migrations, or tightening CI guardrails around risky changes.

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。

Orchestrating migrations, upgrades, and modernization across frameworks, libraries, APIs, databases, and dependencies. Generates codemods, applies Strangler Fig, verifies equivalence, plans rollback.

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。

Designing web-to-iOS/Android porting strategy: feature parity matrices, native architecture maps, phased Strangler-Fig roadmaps. Not for same-language migration (Shift) or native impl (Native).

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Set up Blender cameras with cinematic intent — focal length, depth of field (f-stop / focus object), composition (rule of thirds, leading lines), animated cameras (orbit, dolly, push-in), tracking constraints. Use whenever the user asks to "set up the camera", "frame the shot", "make it look cinematic / hero / portrait / wide-angle / telephoto", "add depth of field", "orbit the camera", or any composition/framing request. Make sure to use this skill even if the user does not say "camera" — also covers "hero shot", "close-up", "from above", "shallow focus", "85mm portrait look".

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。

Detect texture-atlas regions and map each source part to its own UV rectangle or projected UV surface. Use when a texture pack must fit a Blender model 1:1, when textures look off/stretched, when alpha decals or lightmaps are provided, or before exporting a textured GLB for a brand mascot/logo.

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。

Use when the user wants web research: gathering cited, multi-angle evidence on a specific question. Triggers on: "research X for me", "do web research on", "look up sources for", "find citations for", "gather evidence on", "what does the web say about X". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups ("find this function", "search the repo"), local file search, LLM-as-judge evaluation, or paywalled/auth-gated scraping. Produces a written plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced claims.

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。

Coach structured brainstorming sessions on any topic: diverge on ideas together, then converge on priorities and next steps in a session document. Use whenever the user wants ideas or wants to think out loud, in any language ("brainstorm with me", "give me ideas for…", "help me come up with…", "let's explore options for…", "I'm stuck on the name / the features"; Vietnamese "brainstorm cùng tôi", "cho tôi ý tưởng", "nghĩ cùng tôi xem"), even when they never say "brainstorm". Also use when the user wants multiple perspectives or a devil's-advocate pass on their ideas ("give me different angles", "phản biện mấy ý tưởng này", "party mode"). Not for diagnosing why something is failing (problem-solver), user research (design-thinking), or company-level strategic bets (strategy-board).

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Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards. USE THIS SKILL WHEN: - You need to review or audit actuarial models (reserving, pricing, capital) - Someone asks about loss triangle analysis or reserve adequacy - You are evaluating IBNR calculations, chain ladder methods, or Bornhuetter-Ferguson - A project involves insurance pricing, GLM rating models, or ratemaking - You need to assess Solvency II SCR calculations or RBC compliance - Someone mentions actuarial opinions, ASOP compliance, or SOA standards - You are reviewing stochastic models, ESG configurations, or DFA frameworks - A codebase uses actuarial libraries (chainladder, lifetables, ChainLadder R package) TRIGGER PHRASES: "actuarial", "loss reserving", "IBNR", "chain ladder", "premium pricing", "mortality table", "Solvency II", "capital adequacy", "ratemaking", "GLM pricing", "risk-based capital", "reserve analysis", "actuarial opinion"

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。