「bot」の検索結果

Episode and season structure for TV series (剧集单集与季的结构) — teasers and cold opens, broadcast four/five/six-act grids with page anchors, three tests for finding the invisible acts in streaming scripts, act-out and cliffhanger taxonomies, Oberg's four information tools, A/B/C/runner weaving and scene-count ratios, the Calvisi pilot beat sheet, five-part scene structure, and season shape (tentpoles, bottle and container episodes, two-parters, finales). Merged from Calvisi, Douglas, Oberg, Landau, Goldberg & Rabkin, Miller, Rabkin and Blum, plus act lengths measured from published West Wing, Succession, Sopranos, Downton and Fleabag scripts. Use when breaking an episode into acts, deciding how many acts a script needs, placing act outs and cliffhangers, designing a teaser, weaving A/B/C stories and runners, beating out a one-hour pilot, auditing an episode that has no shape, reverse-engineering a show's structure, or planning a season's episode order (分幕、出幕、悬念结局、季弧、瓶子集).

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。

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.

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。

Provides React Navigation UI patterns for stacks, tabs, drawers etc. Use when building navigation UIs with React Navigation, configuring headers, bottom sheets or handling safe areas and insets.

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。

Adversarial Quarto-vs-Beamer parity QA. A critic agent compares the Quarto HTML render to the Beamer PDF benchmark for content/visual parity; a fixer agent applies fixes; loops until APPROVED or two consecutive rounds turn up nothing new (fallback cap 5 rounds). Use when user says "qa the quarto", "check parity", "does the html match the pdf?", "quarto matches beamer?", or after a translate-to-quarto run. Requires both the `.qmd` rendered and a `.pdf` benchmark.

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 dark cinematic SaaS/product motion videos in the Presenton-like "magic UI" style: black starfield stage, bottom purple glow, large kinetic type, cyan-to-magenta CTA buttons, prompt cards, floating UI templates, integration badges, model rings, export objects, speed-blur transitions, and short product capability arcs. Use when the user asks for "这种风格", "同款风格", dark SaaS promo, AI product demo, magic UI product video, or a style-level creation inspired by a reference video. Do not use for pixel-level or frame-accurate replication; use rn-replica-qc first for that.

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 composite HeyGen digital-human videos in the content workspace. Use whenever the user asks for a 数字人, 数字人5, HeyGen, AI 口播人物, 数字人小窗, 圆形头像口播, full-screen digital human, or asks to make a video that uses the existing avatar. Enforce Creator-plan CLI OAuth, the configured Digital Twin, local IndexTTS2 narration, Avatar III for an unspecified digital human but Avatar V whenever the named preset 数字人5 is requested, adaptive face measurement plus the approved human-reviewed visual-centering offset in the headroom_08 circular bottom-left layout unless full-screen is explicitly requested, subtitle-safe placement, credit-aware master reuse, final QC/archive routing, and mandatory pairing with `heygen-avatar-motion` before any motion prompt or paid generation.

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, track and update team goals in Hivemind via the `hivemind` CLI. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.

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。

Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.

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, track, and read team goals via Hivemind from openclaw. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.

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。

Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.

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, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.

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。

Manages work transitions between team members or agents by creating structured handoff documents, summarizing project status, documenting key decisions, blockers, and open questions, and generating onboarding briefs. Use when someone needs to hand off, hand over, or transition a project; pass work to another person or agent; brief a colleague taking over; prepare a shift change summary; or onboard someone mid-task. Produces ready-to-use handoff documents covering current status, next steps, known issues, technical context, and communication templates for both planned and unplanned transfers.

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。

Full-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution. Drawing on twelve classic engineering books. Triggers when: user wants to "fix everything", "sweep the codebase", "auto-fix all issues", "clean up the whole project", or asks for a single command that both diagnoses and remediates quality problems. Do NOT trigger for: read-only audits or health reports where the user only wants findings without code changes; single-dimension reviews (use the focused skill instead: brooks-review / brooks-audit / brooks-debt / brooks-test); server health checks, HTTP /health endpoints, Kubernetes probes, database health, or application uptime.

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。

Find and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object pooling, draw-call batching, fewer allocations/GC spikes, and asset budgets. Engine- neutral method that pairs with each engine's profiler. Use when the user mentions performance, optimize, low/dropping FPS, frame drops, stutter, lag, profiler, frame budget, draw calls, batching, garbage collection/GC spikes, object pooling, or "the game runs slow".

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。

Attribute GPU time in one sglang-omni stage to specific lines of `sglang_omni/` python source. Drives the `llm-torch-profiler-analysis` backend with a mapping/formal trace pair plus steady-state gates, and carries the rules for reading its three tables on an omni stage. Use when a stage is slower than expected and the question is which python code is the bottleneck, not which kernel is hot.

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。

Creates, edits and benchmarks skills; supersedes the official skill-creator plugin, so when both are listed, use this one. Use when the user wants to create or improve a skill or run skill evals, or to distill work into a skill even without saying "skill": 把这次 session 做成一个 skill / 把以前的对话沉淀到 skill 里 / 从我认可的样例里提炼我的喜好.

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。

Send a single one-off message to a WeCom (Enterprise WeChat) group bot. Use this skill whenever the user says "/notify-wecom", "send a quick WeCom message", "企微通知一下", "临时发一条企业微信", or any one-shot notification that does not need a reusable template or setup workflow.

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。

Build a small, coherent opening repertoire that fits your style and level — the few lines actually worth learning, plus the plans and traps behind them. Use when asked what chess opening should I learn, build me a repertoire, help with my openings, or what to play against [opening]. Produces a compact repertoire for White and Black keyed to your rating and style, the main ideas and typical plans (not just moves to memorize), the common traps to know from both sides, and what to study next — kept small enough to actually learn.

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 asked 写8D报告, 客户投诉8D, 质量问题8D, 客诉回复报告, 8D 怎么写, 根本原因分析报告, or write an 8D problem-solving report for a customer complaint or internal quality issue in a Chinese factory. Produces a bilingual (Chinese and English) 8D report from D0 to D8 with the problem described by 5W2H, dated containment actions and suspect-stock quantities, root cause for both occurrence and escape (流出) with 5 Why and fishbone evidence, verified corrective actions, prevention through updated PFMEA, control plan and SOP, and closure criteria, in the format customers expect.

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 a matched Chinese and English CV (中英文简历) from one set of facts: each version follows its own conventions rather than a literal translation, with names, titles, dates, education and company names rendered correctly in both. Use when asked for a Chinese and English resume, translate my CV into Chinese, 中英文简历, 英文简历, or apply to a foreign company in China or a Chinese company abroad. Produces the Chinese CV, the English CV, a consistency table proving the facts match, and a glossary of the terms 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。

Offboard an AI agent the way you'd offboard an employee — inventory what it knew and touched, export then purge its memory, revoke every credential and access grant, and write the handover for its successor (human or agent). Use when decommissioning an agent or bot, switching agent vendors, ending an AI pilot, or when someone asks 'what did this thing have access to?'. Produces a severance checklist, an access-revocation table, a memory disposition record, and a successor handover.

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。

Figure out which AI tool actually fits the task in front of you — chatbot, coding assistant, image model, agent, or none — instead of forcing one tool onto everything. Use when asked which AI tool should I use for, what's the best AI for, do I even need AI for this, or should I use ChatGPT or something else. Produces a match between your task and the right kind of AI tool (with why), the trade-offs that matter for your case, when the answer is a non-AI tool or plain human effort, and how to try it cheaply before committing — so you pick by fit, not by hype or habit.

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。

Help users identify whether supply or demand is their primary growth bottleneck and apply tactical levers to achieve marketplace liquidity and long-term health.

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。

Help users build functional product prototypes from natural language or visual mocks using AI coding tools. This skill enables product leaders to bypass engineering bottlenecks and validate ideas through hands-on building.

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。