Generate faceless content video prompts for Seedance 2.0 on Higgsfield. Use for faceless YouTube channels, TikTok content without showing face, anonymous creator content, narration-driven videos, stock-footage-style AI content, or any video where the creator doesn't appear on camera. Triggers on faceless, no face, anonymous, narration, stock footage, b-roll, background video, voiceover video.
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。
rediumvex/ai-video-generator-claude☆ 4132026年8月11日 更新
Use face_recognition to detect faces, extract landmarks and encodings, compare identities, run the face_recognition and face_detection CLIs, and troubleshoot dlib/model installation.
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。
VectorSpaceLab/AREX-Skill☆ 3322026年9月3日 更新
Interview the user and create an approved GRACE 4 GraceChangeSpec plus optional design-context.xml inside .grace/changes/active/C-*/.
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。
osovv/grace-marketplace☆ 2532026年9月24日 更新
Read an approved GRACE 4 GraceChangeSpec and optional design context, then create a GraceChangePlan with assertions, scopes, tasks, and verification gates.
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。
osovv/grace-marketplace☆ 2532026年9月24日 更新
Think and work like an expert Chemical Oceanographer. Use when a task calls for Chemical Oceanographer judgment. Reasons from seawater thermodynamics, carbonate-system coupling (DIC, TA, pH, pCO2), redox hierarchies, and tracer conservation on density surfaces through CO2SYS/seacarb with Dickson CRMs, Winkler oxygen, IRMS isotopes, GO-FLO clean trace-metal sampling, and GLODAP/SOCAT/GEOTRACES synthesis while treating organic alkalinity, headspace equilibration, pCO2-mooring biofouling, and trace-metal contamination 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☆ 2052026年10月3日 更新
口腔种植 (含 单牙/多牙缺失种植 / 全口 All-on-X / 即刻种植 即刻负重 / 上颌窦提升 / 牙槽嵴骨增量 GBR / 软组织移植 / 数字化种植 (CBCT 设计 + 口扫 + 导板 + CAD-CAM 上部) / 种植体周炎防治 / 种植修复 (基台 + 冠 + 杆卡 + 覆盖义齿) — 不含 普通牙体牙髓 / 正畸 / 儿牙 / 口腔颌面外科肿瘤 / 隐形矫治商业) (implant dentistry — surgical placement and prosthetic restoration of osseointegrated dental implants; covers diagnosis & treatment planning, site preparation (bone augmentation, sinus elevation, soft-tissue grafting), implant placement (delayed / immediate / immediate-loading), provisionalization and final restoration (cement / screw retained, custom abutments, full-arch), digital workflow (CBCT planning, intra-oral scanning, guided surgery, CAD-CAM milled prosthetics), and long-term maintenance including peri-implantitis prevention and treatment; NOT general restorative dentistry, NOT orthodontics, NOT pediatric dentistry, NOT maxillofacial oncology / trauma reconstruction, NOT clear-aligner business.) Master OS — automated mastery of implant dentistry — surgical placement and prosthetic restoration of osseointegrated dental implants; covers diagnosis & treatment planning, site preparation (bone augmentation, sinus elevation, soft-tissue grafting), implant placement (delayed / immediate / immediate-loading), provisionalization and final restoration (cement / screw retained, custom abutments, full-arch), digital workflow (CBCT planning, intra-oral scanning, guided surgery, CAD-CAM milled prosthetics), and long-term maintenance including peri-implantitis prevention and treatment; NOT general restorative dentistry, NOT orthodontics, NOT pediatric dentistry, NOT maxillofacial oncology / trauma reconstruction, NOT clear-aligner business.: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on implant dentistry — surgical placement and prosthetic restoration of osseointegrated dental implants; covers diagnosis & treatment planning, site preparation (bone augmentation, sinus elevation, soft-tissue grafting), implant placement (delayed / immediate / immediate-loading), provisionalization and final restoration (cement / screw retained, custom abutments, full-arch), digital workflow (CBCT planning, intra-oral scanning, guided surgery, CAD-CAM milled prosthetics), and long-term maintenance including peri-implantitis prevention and treatment; NOT general restorative dentistry, NOT orthodontics, NOT pediatric dentistry, NOT maxillofacial oncology / trauma reconstruction, NOT clear-aligner business. problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词:「种植牙」「种植」「口腔种植」「牙种植」「implant」
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。
swaylq/master-skill☆ 1552026年9月6日 更新
Suede Labs cross-surface canon discipline: hold one canonical answer across every surface that states it (web, iOS, Android, docs, a second service) by generating a contract from the reference surface and making the others assert against it, so a divergence fails a test instead of reaching a user or an answer engine. Consistent canon is what makes a product citable: generative search quotes sources that do not contradict themselves, and a number that differs between your site and your app is a contradiction a model can see. Use when the same rule, threshold, ladder, or stated fact lives on two or more surfaces; when values are copied by hand out of a handoff; when two surfaces already disagree; or when auditing where they drifted. NOT FOR: deciding which surface is correct (a product call this skill records rather than makes); reviewing a diff (use suede-code-review); wiring merge gates (use suede-ci-gate); a generative-search audit of a page (use suede-seo-audit).
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。
JasonColapietro/suede-creator-skills☆ 1272026年10月12日 更新
Present pathway options and orchestrate place-based curriculum design from a local place, curriculum requirement, or community issue. Use when place should become a primary text for learning.
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。
nota-america/forgecat-agent-profiles☆ 902026年9月24日 更新
VictoriaTraces provider for obz. Covers trace search, trace retrieval by ID, and extension commands for service and operation discovery via the Jaeger-compatible HTTP API. This skill should be used when the user mentions "VictoriaTraces", "obz trace -p vt", or needs to search distributed traces from a VT backend.
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。
alibaba/obz-cli☆ 282026年7月12日 更新
Place pre-screened literature citations into a LaTeX or Word manuscript, or restyle the citations already in one. Three modes: (1) inline placement — inline \cite{}/\citet{}/\citep{} with a compiled references.bib, for author-date journals (APA, MLA, Harvard, Chicago author-date, IEEE, Vancouver); (2) footnote placement — full formatted \footnote{} or OOXML footnotes for legal and notes styles (Bluebook, OSCOLA, Chicago, APA, McGill) with Id./supra short forms; (3) restyle — convert existing footnote citations from one style to another. This skill is manual-invoke ONLY — trigger ONLY when the user explicitly runs /cite-placement or explicitly names the "cite-placement" skill. Do NOT auto-trigger on general citation, footnote, or reference requests.
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。
kennethkhoocy/applied-micro-skills☆ 222026年9月5日 更新
Use when the user provides a Facebook URL or asks to read personal posts, comments, reactions, friends, timelines, profiles, stories, feeds, groups, events, or saved items, or to publish personal text posts, comments, and replies, or to discover public events happening near a place, nearby, or in a local area on a date, or to create, edit, publish, or delete their own Marketplace listings. To find, browse, or buy Marketplace listings, use shopping instead. Use pages commands for managed Facebook Page discovery, insights, native draft editing/deletion, same-draft publication, approved posts and native scheduling.
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。
obra/muse-skills☆ 202026年10月13日 更新
Scans CopilotKit's public product / pricing / Premium pages at the start of every weekly report to produce the authoritative list of COMMERCIAL surfaces (Premium · CopilotKit Enterprise · Intelligence Platform · paid tiers) and detect any newly-added or changed commercial feature since last week. This list defines what the report's 🏢 Enterprise section is about — CopilotKit's commercial/paid product, NOT "CopilotKit running inside an enterprise company." Emits the surface list + a free-vs-paid classifier the report uses to decide "does this issue hit a commercial surface?", plus a diff of what changed. Runs as a subagent (many web fetches) so the orchestrator's context stays small. Invoked by weekly-report (spawned at report start) and the enterprise skill; also triggers on "scan product surfaces", "what's premium", "commercial surfaces", "did we add a premium feature".
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。
CopilotKit/outpost☆ 122026年10月9日 更新
gogcli(gog コマンド)の専門家スキル。Google Workspace と関連サービス25以上(Gmail, Calendar, Chat, Drive, Sheets, Docs, Slides, Tasks, Keep, Contacts, People, Groups, Admin, Classroom, Forms, Meet, Maps, YouTube, Photos, Sites, Analytics, Search Console, Apps Script, Zoom)をターミナルから操作するGoベースCLIツールの使い方を支援。OAuth2/サービスアカウント認証、マルチアカウント管理、自動化・エージェント安全機能を提供。Use when working with Google Workspace services via CLI, managing Gmail/Calendar/Drive/Sheets, automating Google Workspace tasks, or setting up gogcli authentication.
takusaotome/claude-skills-library☆ 92026年10月5日 更新
Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.
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。
bg-szy/TOP-SKILLS☆ 62026年9月8日 更新
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
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。
bg-szy/TOP-SKILLS☆ 62026年9月8日 更新
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
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。
bg-szy/TOP-SKILLS☆ 62026年9月8日 更新
ABSOLUTE MUST to debug and inspect LLM/AI agent traces using PostHog's MCP tools. Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly, verify context/files were surfaced, inspect subagent behavior, investigate LLM decisions, or analyze token usage and costs. Also use when raw SQL/HogQL against `events.properties.$ai_input` / `$ai_output_choices` returns empty — message content lives only on the dedicated `posthog.ai_events` table.
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。
0xAidan/polymarket-bot-test☆ 42026年9月4日 更新
Append structured execution traces across operational, cognitive, and contextual surfaces with minimal overhead. Load when inspecting agent runs, logging tool calls and observations, enabling post-run debugging, or pairing with structured-planning step IDs. Also triggers on "trace this run", "log execution", "agent observability", "run log", or when fault-localize needs evidence. Default-on during multi-step plans. Traces live at .agent-loom/traces/ — git-ignored by default.
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。
dvy1987/agent-loom☆ 32026年8月8日 更新
Lifecycle for AI Matrx agent-aware UI surfaces. Use when creating a surface in features/surfaces/manifests/, or completing or repairing one that is partial, stubbed, unregistered, missing runtime context or context menus, or not agent-wired. NOT for certifying a surface (use surface-check).
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。
armanisadeghi/ai-matrx☆ 32026年10月13日 更新
Generates PSR-17 HTTP Factories implementation for PHP 8.5. Creates RequestFactoryInterface, ResponseFactoryInterface, StreamFactoryInterface, UriFactoryInterface, ServerRequestFactoryInterface, UploadedFileFactoryInterface. Includes unit tests.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
ルーターやスイッチ、Linuxの通信エラーや切断を調べ、両端の設定とエラー件数の増え方から、ケーブル不良や混雑などの原因を切り分けるスキル。
- 通信の途切れやパケット損失を調べたいとき
- スイッチのCRC増加を調べたいとき
- リンク両端の設定を比較したいとき
affaan-m/ECC☆ 27.8万2026年10月12日 更新
MemPalace — Local AI memory with 96.6% recall. Semantic search, temporal knowledge graph, palace architecture (wings/rooms/drawers). Free, no cloud, no API keys.
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。
MemPalace/mempalace☆ 6万2026年10月13日 更新
Create, hand off, claim, execute, and close agent tasks through the MemPalace logstream. Use when the user wants to delegate work, prepare a ready-to-paste task for another agent, receive a MemPalace task id, or explicitly launch a supported headless agent in controlled mode.
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。
MemPalace/mempalace☆ 6万2026年10月13日 更新
Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.
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。
github/awesome-copilot☆ 4万2026年10月12日 更新