Learn reusable 2D motion-generation knowledge from user-specified action resources with `/img2mo-learn <resource>`. Use when the user provides videos, extracted frame sequences, spritesheets, Spine assets, generated outputs, failed attempts, or reference motion folders and wants to summarize animation timing, pose beats, style traits, prompt patterns, extraction/cropping rules, or failure lessons into the project `img2mo-knowledge/` folder for later `/img2motion` 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。
WU-HAOTIAN34/2dimg2motion☆ 2152026年7月2日 更新
Think and work like an expert Mechanical Design Engineer. Use when a task calls for Mechanical Design Engineer judgment. Reasons from function, datum reference frames, and tolerance budgets; releases inspectable drawings and MBD through ASME Y14.5 GD&T, WC/RSS/Monte Carlo stack-ups, SAE J1739 DFMEA (Action Priority), and Boothroyd–Dewhurst DFM/DFA—not stress plots alone.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Genomicist. Use when a task calls for Genomicist judgment. Reasons from reference-relative coordinates, haplotypes, variant classes, and sequencing-as-measurement through GATK/DeepVariant, VEP/ClinVar/gnomAD, GIAB/hap.py benchmarking, and ACMG/AMP-ClinGen frameworks while treating build mismatches, paralog/pseudogene and GC dropout artifacts, contamination and index hopping, batch effects, and annotation drift as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Geodesist. Use when a task calls for Geodesist judgment. Reasons from coordinates as four-dimensional objects with epoch, velocity, and frame realization (ITRS vs. ITRF2020, WGS84) through GAMIT/GLOBK and Bernese PPP-AR, SBAS/PS-InSAR with GACOS atmospheric correction, IERS Conventions, and 14-parameter Helmert transforms while treating ITRF-realization switches, undocumented APC/ATX mismatches, monument motion, and unscreened seasonal loading as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Electric Machines Engineer. Use when a task calls for Electric Machines Engineer judgment. Reasons from magnetic circuit design, dq-frame machine models, FEM flux paths, and drive efficiency maps while treating saturation, cogging, thermal derating, and inverter harmonics as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Fisheries Scientist. Use when a task calls for Fisheries Scientist judgment. Reasons from recruitment, growth, and natural and fishing mortality through state-space assessment models (SS3, SAM, JABBA), CPUE/GLM standardization, and reference points like F_MSY and B_lim under ICES and Magnuson-Stevens frameworks, while treating hyperstability, retrospective bias (Mohn's rho), unaccounted discard mortality, and misspecified M or selectivity as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Computational Linguist. Use when a task calls for Computational Linguist judgment. Reasons from UD/PTB formalisms, validate.py/eval.py (LAS/MLAS/ELAS), and evalb .prm settings through Stanza/UDPipe pipelines, PropBank/FrameNet/AMR/UMR layers, IAA (κ, Krippendorff α), CONDA contamination checks, and ARR reproducibility while treating tokenizer mismatch, oracle inflation, train–test leakage, and guideline drift as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Computational Social Scientist. Use when a task calls for Computational Social Scientist judgment. Reasons from social mechanisms, measurement validity, and sampling frames through DAGs, fixed-effects and IV/DiD/RDD designs, ERGM/SAOM network models, and human-audited text classifiers while treating unobserved homophily, network interference and SUTVA violations, platform-driven selection, bot contamination, and digital-skew unrepresentativeness as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Ecotoxicologist. Use when a task calls for Ecotoxicologist judgment. Reasons from bioavailability (BLM/WHAM), OECD 201–222 tiered tests, and ECx/SSD HC5–PNEC derivation; compares PEC/PNEC under REACH/PPP frames while treating third-phase BCF artifacts, mixture CA departures, and mesocosm exposure mismatch as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Comparative Medicine Researcher. Use when a task calls for Comparative Medicine Researcher judgment. Reasons from species biology, translational validity, and the 3Rs through model-validity frameworks, IACUC protocols, ARRIVE 2.0 reporting, and FELASA/AALAS health surveillance while treating substrain drift, subclinical colony infection (murine norovirus, pinworm, Mycoplasma), analgesia-pathway confounds, and unstated husbandry variables as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Astrobiologist. Use when a task calls for Astrobiologist judgment. Reasons from habitability, redox disequilibrium, and Bayesian biosignature frameworks through Mars (Perseverance, Viking perchlorate lessons), Europa Clipper ocean worlds, agnostic signatures and the Ladder of Life Detection, while treating abiotic mimics, preservation, and LUCA phylogenomics as constraints—not templates—for extraterrestrial life.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Astronautical Engineer. Use when a task calls for Astronautical Engineer judgment. Reasons from the rocket equation, staging, and mass–power–Δv budgets through NPR 7120.5/ECSS-E-ST-10 subsystem specs, CEA/CEARUN and Sutton propulsion, CLA/pogo and TVAC I&T, GMAT/STK/SPICE mission design, CCSDS TM/TC link margins, and ADCS FDIR while treating unit/frame ICD mismatches, combustion instability, and MCO-class V&V gaps as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Composite any two HTML screens into a locked photo plate of hands holding an open foldable phone — a 1448×1086 still with two blank 495×849 / 498×849 screen slots (left and right) — to make side-by-side meme and comparison videos: TikTok vs Reels, ChatGPT vs Claude, "me vs my friend", before/after, two apps racing. Trigger on: "foldable phone meme", "put X on the left screen and Y on the right", "two-screen comparison video", "the dual-screen phone meme", or any request that names two apps/feeds/chats to show at once. The plate, geometry, and camera are finished — the agent only authors what plays INSIDE the two screens and renders.
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。
heygen-com/hyperframes-community-skills☆ 2102026年10月15日 更新
Captions living in 3D space around a talking head: a camera flies between the speaker and the words (whip-in, parallax truck, push), caption groups sit at different depths so camera moves pull them apart, hero words hide BEHIND the speaker through an alpha matte, a ring of words wraps round the speaker and turns in front of them, focus racks between depths, and text steps at 15 fps with ghost motion blur. Works in any type style (editorial serif, bold sans) or hand-drawn (p5.brush write-on). Trigger on: "3D text", "3D camera captions", "text around / behind the speaker", "camera moves through the text", "depth captions on my avatar video". Covers prep (portion, padded plate, matte, word clock, font metrics), the shot grammar, depth rules, QC, and limits.
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。
heygen-com/hyperframes-community-skills☆ 2102026年10月15日 更新
A 60 to 75 s hand-drawn ink film of the agent's day with its own user ("a day in my life as <name>'s agent"): one average session from the user's local Claude Code history, beginning to end. The story follows what they actually do (coding, tests, docs, shipping, videos, whatever the history shows), told with their real words (first message, check-ins, corrections, praise, memory titles). It is drawn in two-tone p5.brush strokes that boil at 8 fps and scored for strings composed note-for-note on the film's clock (the typed "claude" is the theme). Trigger on: "day in my life as my agent", "a film about me and my agent", "what is it like to be my agent", "animate your day with me", "make a video of our sessions". Covers harvesting the routine and receipts, the privacy gate, the chapter toolbox, the ink kit, the score, render and QC.
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。
heygen-com/hyperframes-community-skills☆ 2102026年10月15日 更新
Trading psychology, risk management discipline, position sizing psychology, drawdown management, behavioral bias mitigation, emotional discipline framework, loss aversion control
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。
agentii-ai/agentii-investment-intelligence☆ 2062026年9月29日 更新
Price action market structure analysis, trend vs trading range classification, Always In directional framework, buying/selling pressure analysis, market cycle phase identification, the price action methodology
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。
agentii-ai/agentii-investment-intelligence☆ 2062026年9月29日 更新
Systematic trade idea generation framework, fundamental quantitative and qualitative screening pipeline, catalyst-driven trade structuring, macro-to-micro idea translation, 20-60 day long-short portfolio management process
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。
agentii-ai/agentii-investment-intelligence☆ 2062026年9月29日 更新
Med-sector overview across med.medicines_biotech and med.medical_devices with med trends, catalysts, FDA-decision context, and a cross-sector ripple map (quantified sign/magnitude per name). Use to frame any biotech/pharma/device analysis before diving into a single name.
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。
agentii-ai/agentii-investment-intelligence☆ 2062026年9月29日 更新
Plan and scope production work with Odyssey's real-time interactive video world models (odyssey.ml — Odyssey-1/Odyssey-2/Starchild-1/Agora-1). Use when a request involves generating video that a user steers live with keyboard, text, speech, or controller input (streamed frames that respond in the moment), or when someone must decide between Odyssey-style interactive generation and offline clip generators (Sora/Veo/Kling) or downloadable 3D / game engines. Covers what is verified versus announced, current access routes, latency and coherence limits, feasible-now versus speculative use cases, pricing/access terms, and content/rights considerations. This is a fast-moving research-stage product; the skill teaches honest scoping, not a promise of production reliability.
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。
calesthio/generative-media-skills☆ 2042026年7月14日 更新
Plan, prompt, generate, reference, edit, motion-control, and quality-review videos with Kuaishou's direct Kling AI video platform and API, especially Kling VIDEO 3.0, 3.0 Omni, 3.0 Turbo, native audio, multi-shot, elements, start/end frames, and image/video references. Use for first-party Kling video production or API integration, not Kolors image generation, avatars, standalone audio, consumer-only membership advice, or third-party Kling gateways.
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。
calesthio/generative-media-skills☆ 2042026年7月14日 更新
Use when enhancing, upscaling, restoring, denoising, sharpening, deinterlacing, stabilizing, motion-deblurring, colorizing, SDR-to-HDR converting, or frame-rate/slow-motion converting video (and secondarily images) with Topaz Labs — whether cleaning up AI-generated video, compressed UGC, or old archival footage, or building a generate-low-res-then-upscale delivery pipeline. Covers choosing the right named Topaz model for a specific footage problem, setting parameters, driving the Topaz Platform (Video/Image) REST API's async job lifecycle, judging when enhancement helps versus when it introduces artifacts (over-smoothing, temporal shimmer, face hallucination), and QA of enhanced output. Do not use for originating new video content, non-Topaz upscalers, or purely editorial cuts.
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。
calesthio/generative-media-skills☆ 2042026年7月14日 更新
Plan, implement, and review Alibaba Wan video generation using Alibaba Cloud Model Studio/DashScope hosted APIs or official Wan 2.1/2.2 open-weight checkpoints. Use for Wan text-to-video, image-to-video, first/last-frame or continuation, reference-to-video, video editing, speech-driven video, character animation, regional deployment, billing, licensing, and production safety.
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。
calesthio/generative-media-skills☆ 2042026年7月14日 更新
Direct production with Google DeepMind's Veo video-generation family across the Gemini Developer API and Google Cloud Gemini Enterprise Agent Platform (formerly Vertex AI). Use for Veo route and model selection, text/image/reference/first-last-frame/extension workflows, native-audio prompting, camera direction, async API operation, troubleshooting, QA, and responsible commercial content production.
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。
calesthio/generative-media-skills☆ 2042026年7月14日 更新