'beats' 검색 결과

Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, NeuralPLexer, and hybrid workflows (DiffDock pose + GNINA rescore + PoseBusters QC). Explicit handling of when ML beats classical docking, when classical beats ML, the PB-invalid pose problem, and rescoring as the standard production hybrid. Use when modern docking is needed: foundation-model ligand-pose prediction, AI rescoring of classical poses, or scaffold-hopping in cross-docking scenarios.

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Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, NeuralPLexer, and hybrid workflows (DiffDock pose + GNINA rescore + PoseBusters QC). Explicit handling of when ML beats classical docking, when classical beats ML, the PB-invalid pose problem, and rescoring as the standard production hybrid. Use when modern docking is needed: foundation-model ligand-pose prediction, AI rescoring of classical poses, or scaffold-hopping in cross-docking scenarios.

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Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, NeuralPLexer, and hybrid workflows (DiffDock pose + GNINA rescore + PoseBusters QC). Explicit handling of when ML beats classical docking, when classical beats ML, the PB-invalid pose problem, and rescoring as the standard production hybrid. Use when modern docking is needed: foundation-model ligand-pose prediction, AI rescoring of classical poses, or scaffold-hopping in cross-docking scenarios.

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Audits an Articles of Agreement contract — the daemon-witnessed agreement every official Port Daddy agent signs covering registration, transcript reporting, tool-use gating, file claims, parley conduct, budget limits, and operator control — against the enforcement-beats-hope bar: a clause counts as safe only when it resolves to a concrete, daemon-observable mechanism with a defined denial shape, never a promise the agent might honor. Use when drafting a new agent's Articles, reviewing a compliance-level (C0-C6) claim, deciding whether a clause is genuinely enforced or merely documented, or auditing whether an agent's claimed identity can be trusted. NOT for securing the inbound event-to-spawn path (fleet-event-spawn-trust), designing the relay's transport PKI and signing keys (pd-relay-zero-trust), or tracking an agent's identity and reputation across its whole lifetime after it signs (agent-identity-continuity-reputation).

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macOS의 OpenClaw를 main 최신 상태로 업데이트하고 Gateway와 앱을 확인합니다. 자동 검사 실패 수정과 실제 배포 없는 전체 릴리스 검증도 수행합니다.

• macOS의 OpenClaw를 업데이트합니다
• 업데이트 후 Gateway와 앱을 확인합니다
• 현재 main의 자동 검사 실패를 수정합니다

Handle tasks managed by Paperclip by reading their context, saving documents and deliverable files, updating progress and blockers, and coordinating delegated work. The skill provides procedures for short agent runs, approvals, and traceable task updates.

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• Resuming assigned work with its latest task context
• Delivering documents and downloadable files on a task
• Recording completion, dependencies, or pending questions

Estimate the cost per million tokens, units of model text, on hardware you own using power consumption, electricity rates, hardware costs, and measured generation speed. Compare utilization levels to find when local operation costs less than a hosted model.

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• Compare local model costs with a hosted API
• Estimate costs at different utilization levels
• Include electricity and hardware depreciation in costs

Generate short videos with audio from prompts and reference images, then refine them through conversational edits. The skill covers targeted object, lighting, and text changes, plus timed actions, using Gemini Omni Flash through documented video tools.

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• Creating short videos with sound from written prompts
• Assigning reference images to characters, products, or styles
• Refining objects, lighting, and text through conversation

Guide HyperFrames video projects from setup and component selection through checks, previews, and rendering. Use command-line tools to inspect timelines, diagnose failures, compare frames, and choose local, batch, or cloud rendering for the finished composition.

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• Set up and preview a HyperFrames video project
• Diagnose build or rendering failures
• Render multiple videos from variable data

Turn music into a lyric video, slideshow, or animated promo, timing visuals to beats or musical phrases. Use supplied photos and clips, or build with text and templates, then preview and render an MP4.

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• Creating a lyric video timed to a song
• Turning photos and clips into a music-driven slideshow
• Making an animated promo with text and templates

Analyze captured network traffic and binary messages to recover custom protocol structures. The skill organizes message types, fields, and connection states, then produces reproducible decoding steps with supporting evidence for authorized investigations.

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• Recover message fields from captured network traffic
• Investigate unknown Protobuf message structures
• Map handshakes, heartbeats, and connection states

Manage coding agents and their workspaces in Paseo through its tools or command line. This reference covers project registration, workspace scripts, agent settings, recurring tasks, and reminders that return to the current conversation.

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• Creating separate workspaces for development tasks
• Starting and stopping configured workspace scripts
• Launching agents and adjusting their runtime settings

Build interactive dashboards, forms, and visualizations over the QM web interface using HTML, CSS, and JavaScript. Panels can send input to the conversation, update in place, or remain visible across sessions when requested.

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• Display an interactive dashboard over a conversation
• Collect input through forms and buttons
• Explore information through visualizations

Record a game mod with its own audio, or combine existing clips into a short showcase for X or YouTube. Select highlights from timestamped image grids, then add animated titles, credits, transitions, music, and a watermark.

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• Recording a game mod demo
• Cutting a short trailer from gameplay highlights
• Combining existing clips with creator credits

音乐卡点视频 / 踩点视频：检测背景音乐的节拍，让图片或片段在节拍点上切换，配推进/白闪特效，做出燃系'卡点'短视频。当用户说 卡点视频、踩点视频、音乐卡点、节奏卡点、按音乐切换、鼓点视频、踩节奏、beat 卡点、图片卡点、卡点混剪 时使用。基于 shared/scripts/beatsync.py（librosa 节拍检测）。与 slideshow-video 区别：slideshow 每图固定时长、柔和转场，本 SKILL 切换点由音乐节拍决定、硬切踩点带特效。

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Use this skill when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVP_Digest) onto DOCA SHA hardware without rewriting against doca-sha. Covers engine load mechanics (`openssl engine dynamic`, `set_pci_addr` ctrl, `-engine_impl`), the SHA-224 negative test that proves offload engaged, the message-size window where offload beats CPU SHA, and engine-vs-library selection. Trigger even when the user does not say "DOCA SHA Offload Engine" or "OpenSSL ENGINE" — typical implicit phrasings: "speed up openssl SHA on BlueField", "offload SHA without code changes", "is openssl using the accelerator or falling back to software", "prove DOCA SHA actually ran", "openssl dgst hashed but I'm not sure it was offloaded". Refuse and route elsewhere for new SHA pipelines (use doca-sha), MD5 / SHA-3 / SHA-224 / HMAC-SHA offload, incremental hashing via chained `EVP_DigestUpdate`, or OpenSSL PROVIDER authoring.

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[omh] Fine-tuning a model on your own data -- SFT, DPO, RLVR or a LoRA adapter: decide first whether prompting or retrieval already closes the gap, choose the method from the data you have, and promote a checkpoint only when it beats the untuned baseline on a held-out eval. Use when the user says: model-finetuning, model finetuning, model fine-tuning, fine-tune a model, fine-tune the model, fine tune a model, fine tune the model, fine-tune.

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Make short product / skill motion videos (10–30 s, narrated feature demos up to ~60 s) the way high-end launch clips are made — kinetic type, real UI as the material, a hand that causes every reaction, beats that carry into each other instead of replacing each other, hard cuts only where they mean something — without HyperFrames or Remotion. A single HTML composition where every value is a pure function of time, built from a library of measured moves (springs, entrances, carries, contact, camera), rendered frame by frame with real shutter motion blur (1080p30 drafts, 4K60 final), with synthesised sound effects that share one room and an oracle that fails a slideshow before a human has to watch it. Use for 做个动效短片 / 产品宣传片 / 介绍视频 / 发布视频 / 15 秒 launch video / 给 skill 或 app 做个视频 / promo / teaser, for turning real pages or screen recordings into a cut, for product feature demos (产品功能演示 / 功能展示动效) where the UI is rebuilt in HTML from screenshots instead of screen-recorded (不录屏 / 复刻界面 / 截图还原 UI), for narrated cuts with voice-over and subtitles (配音 / 字幕 / 换配音) and for the same film in other languages (日语版 / 多语言 / 本地化), for adding motion vocabulary (动效库 / 转场 / 衔接), and for auditing why a motion video reads as a slideshow (像 PPT / 没节奏 / 一个一个展示 / 转场生硬).

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Use this skill when writing analytical SQL over time-series data with the TimescaleDB Toolkit (timescaledb_toolkit extension) hyperfunctions: approximate percentiles, statistical summaries, time-weighted averages, counter/gauge rates, uptime/heartbeat tracking, state durations, OHLC candlesticks, approximate distinct counts, top-N, and downsampling. **Trigger when user asks to:** - Compute percentiles/medians/p95/p99 over large or rolled-up time-series data - Compute rates or deltas from monotonic counters (Prometheus-style) or gauges - Compute time-weighted averages or integrals over irregularly sampled data - Track uptime/downtime from heartbeats, or time spent in each state - Build OHLC/candlestick or VWAP data for financial ticks - Store re-aggregatable summaries in continuous aggregates (two-step aggregation, rollup) - Approximate COUNT DISTINCT, find top-N / most frequent values, or downsample for charts **Keywords:** timescaledb_toolkit, hyperfunctions, percentile_agg, uddsketch, tdigest, approx_percentile, stats_agg, time_weight, counter_agg, gauge_agg, heartbeat_agg, state_agg, candlestick_agg, hyperloglog, approx_count_distinct, min_n, max_n, mcv_agg, lttb, asap_smooth, rollup, two-step aggregation

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Write a YouTube video script from a raw idea - hook options off 21 formulas, scored, then the full spoken script with the retention beats marked. Use whenever the user wants a video script, a hook, an opening line, "what should I say", "write my next video", or is about to record and does not have the first fifteen seconds yet.

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Genre anatomy from John Truby's The Anatomy of Genres (类型解剖 / 类型节拍 / 混合类型 / 超越类型) — genres as beat systems with a life philosophy underneath; three rules (hit every beat of your genre, mix three or four genres, transcend the primary genre), the ladder and families of twelve genres (Horror 恐怖, Action 动作, Myth 神话, Memoir and Coming-of-Age 回忆录与成长, Science Fiction 科幻, Crime 犯罪, Comedy 喜剧, Western 西部, Gangster 黑帮, Fantasy 奇幻, Detective and Thriller 侦探与惊悚, Love 爱情), each with its hero/opponent/world/plot-shape template, beat list, hard rules with failure conditions, subgenres and transcendent paths, plus a genre-mixing worksheet and a diagnostic. Kept beside sw-truby-anatomy and the Field/Snyder page maps. Use when choosing or confirming a script's genre, when a genre story feels generic or misses the beats its audience expects, when mixing genres, when a horror lacks pressure, an action lacks plot, a love story lacks opposition or a detective story lacks reveals.

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Story structure for screenplays and stage plays (故事结构) — merged from Syd Field's paradigm and plot points, Blake Snyder's Save the Cat beat sheet and board, Robert McKee's Story (event/scene/sequence/act, inciting incident, progressive complications, crisis-climax-resolution, subplots, story triangle), Julian Hoxter's nine-beat model, Neill Hicks' three acts as attraction/anticipation/satisfaction, and Lu Jun's Chinese short-play structure (凤头猪肚豹尾, 起承转合, eight openings, eight endings, 入戏要快/脉络要清/高潮要高/转变要顺/变化要多). Use when outlining a script, placing plot points and midpoint, fixing a saggy second act, designing an opening or ending, diagnosing "nothing happens", choosing between linear and non-linear designs, or converting a premise into beats and cards.

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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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Build the storyline and slide structure for a board presentation. Use when asked to create a board deck, board presentation narrative, board meeting slides, or quarterly board update. Produces a complete slide-by-slide structure with narrative beats, talking points, and slide content guidance.

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