「vin」の検索結果

Recover Vine video metadata (author, user ID, title, thumbnail) from vine.co oembed endpoint even though the Vine API and pages are dead. Use when: (1) you have Vine shortcode URLs (vine.co/v/XXXXX) and need to identify the creator, (2) the Vine page only shows a loading spinner, (3) archive-api.vineapp.com returns 404, (4) need to map Vine shortcodes to user IDs for cross-referencing against the divine.video database. The oembed endpoint is a still-live metadata oracle for the otherwise-dead Vine platform.

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Use when starting work in any divine-* repo (divine-web, divine-mobile, divine-funnelcake, keycast, divine-blossom, divine-router, etc.) or when you've learned a cross-repo fact worth sharing back. The shared divine-context handbook at ~/code/divine/divine-context/ is the source of truth for cross-cutting architecture, Nostr usage, terminology, and the project catalog across the ~50 divine-* repos.

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CodexとDevinがMCPまたはCLIで直接対話し、調査・実装・レビュー・修正を進める。Devinとの対話的な開発を依頼されたときに使い、質問への回答と成果の確認を往復しながら、許可されたPR作成・採用まで進める。Cloudでは公式MCP、手元のファイルや環境ではDevin CLIを使う。Devinの画面操作を指定された場合はdevin-browser-prを使う。

Itôで予約済みのGPUを使ったモデル配信の相談に対し、現状の未対応範囲と将来必要な確認事項を整理するスキル。現在は配信を開始せず、制約を案内します。

• Itô GPU予約後の配信対応を確認したいとき
• OpenAI互換の接続先の制約を知りたいとき
• 将来のモデル配信設定を確認したいとき

[omh] Self-hosted LLM serving on GPUs: choose the serving engine and quantization from decision tables, prepare deployment as an idempotent runbook with observed-only verification, and measure the endpoint with the standard TTFT/TPOT/goodput protocol. Use when the user says: inference-serving, inference serving, serve this model, serve the model, model serving, serving endpoint, vllm, llama.cpp.

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DevinへのGitHub作業の委譲と成果をCodex内ブラウザで確認し、レビュー・修正依頼・PRマージ・環境提案の採用・ローカル同期まで進める。画面での確認や操作を含むDevinへの依頼・成果採用に使う。送信や回答の取得には公式Devin MCPを優先し、相談だけ・PR作成まで等の指定を守る。

Build, migrate, and deploy Next.js apps on Cloudflare Workers with vinext. Use when starting a Next.js project on Cloudflare, moving an existing app to Workers, choosing between vinext and OpenNext, or setting up vinext for Workers. For setup, migration, or deployment, install vinext's upstream skills with `npx skills add cloudflare/vinext` if missing, then read and follow the applicable skill and docs.

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, migrate, and deploy Next.js apps on Cloudflare Workers with vinext. Use when starting a Next.js project on Cloudflare, moving an existing app to Workers, choosing between vinext and OpenNext, or setting up vinext for Workers. For setup, migration, or deployment, install vinext's upstream skills with `npx skills add cloudflare/vinext` if missing, then read and follow the applicable skill and docs.

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Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset correction, crop, normalizeTimestamps, convertTimestamps. Also: compute actor tracks from lidar when no annotations exist, attach camera/lidar mounting + intrinsics, export to MAT/workspace/timetable/script. Use for raw driving dataset files (KITTI, nuScenes, Waymo, Pandaset, ROS/ROS2 bags, .mat, .csv, .mp4) or driving/vehicle/sensor logs that need wrapping. drivingLogAnalyzer (DLA) is OPT-IN ONLY — invoke only on explicit user request ('DLA', 'open in DLA', 'inspect/explore/analyze the recording') or reported sensor problem (sync drift, timestamp mismatch, overlay misalignment). NEVER auto-launch DLA after wrapping (Rule 0). For 'build scenario / export to RoadRunner / drivingScenario / OpenSCENARIO / Unreal / simulate', hand off to matlab-use-scenario-builder.

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Fix "blocked: event rejected by relay policy" errors when publishing Kind 34236 (video) events to divine relays. Use when: (1) Kind 0 profile events succeed but Kind 34236 fails, (2) Generic policy rejection with no specific reason, (3) Video events work on other relays but fail on divine relays. The divine relay requires thumbnails for all video events - stricter than NIP-71 spec.

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Devin CLIから /handoff でDevin Cloudにタスクを引き継ぐ際に発動。ハンドオフ先のDevin Cloudに対して、タスクの実行をCursor Cloud Agentに委譲するよう指示を含める。

Extract a VIN from a photo or image URL using the CarsXE VIN OCR API. Use this when a user shares an image of a vehicle or VIN plate and wants to identify the VIN.

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。

Recover content from "dead" CDNs where DNS no longer resolves but servers still respond. Use when: (1) A service shut down but you have URLs to their CDN, (2) DNS lookups fail but you suspect the CDN provider (Fastly, CloudFront, Akamai) still has the content, (3) Archiving content from defunct services like Vine, Tumblr, etc. The key insight: CDN providers often keep serving content long after DNS dies - hit the IP directly with the original Host header.

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Agent fallback for CCSPlayer_MovementServices_CheckMovingGround (auto-generated, category: vfunc). Locate CCSPlayer_MovementServices::CheckMovingGround in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CCSPlayer_MovementServices_CheckMovingGround, CCSPlayer_MovementServices::CheckMovingGround

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。

PyTorchのモデルや学習コードを作成・点検し、データ読み込み、実験の再現性、学習状態の保存、GPUメモリや処理速度の改善を支援するスキル。

• PyTorchの学習コード作成・レビュー
• 実験結果が揃わない原因を調べたいとき
• 読み込み速度やGPUメモリの改善

Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.

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Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface extraction, 3D asset generation, static-object placement, point-cloud georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization — route those to matlab-import-driving-data.

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Use when reviewing, improving, or refactoring Java object-oriented design, including applying SOLID, DRY, or YAGNI; improving classes and interfaces; correcting encapsulation, inheritance, or polymorphism; resolving God Class, Feature Envy, or Data Clumps; and improving object creation, methods, or exception contracts. Triggers include review Java OOD, refactor Java OOD, improve Java OOD, fix OOP misuse, and identify Java code smells. Part of Plinth Toolkit

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smina molecular docking CLI. AutoDock Vina fork with customizable scoring functions, native SDF/MOL2/PDB ligand input, autoboxing, local energy minimization, and per-atom score breakdowns. Pipeline: receptor PDBQT prep -> ligand prep (RDKit/OpenBabel) -> dock via autobox or explicit grid -> rescore/minimize with custom scoring -> rank poses by affinity. Choose smina over Vina when you need custom scoring terms (--custom_scoring), local optimization of an existing pose (--local_only), per-atom contributions (--atom_term_data), or SDF/MOL2 ligands without manual PDBQT conversion. For unknown binding sites use diffdock; for the Python-bindings/Vinardo workflow use autodock-vina-docking.

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Use when querying or calling pay-per-token foundation models, or when creating, updating, listing, or querying Unity Gateway (also called Unity AI Gateway) services, including model provider services, MCP services, system.ai services, and three-part Unity Catalog service names (catalog.schema.service). Also use for managing spend budgets and usage alerts on Unity Gateway, and for migrating from legacy AI Gateway. Also use when a workload with Model Serving endpoint permissions (for example CAN_QUERY) gets PERMISSION_DENIED querying a three-part model name, since serving-endpoint access does not grant access to a Unity Gateway service. Not for configuring legacy AI Gateway on Model Serving endpoints; use databricks-model-serving for that.

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Analyze Figma designs and translate them into Flutter code using existing divine_ui components and VineTheme. Use when implementing UI from Figma mockups or when checking if a component already exists before building new. Invoke with /figma-designer.

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。

Apply systematic problem-solving methodologies to complex challenges. Use when the user says "guide me through structured problem solving" or "I want to crack this challenge with guided problem solving techniques"

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Automate and script DaVinci Resolve workflows. Use when a user asks to script DaVinci Resolve via Python/Lua API, automate color grading, batch render projects, manage timelines programmatically, automate media import, build render queues, create Fusion compositions via script, automate Fairlight audio processing, manage project databases, build custom tool scripts, or integrate Resolve into production pipelines. Covers the Resolve Scripting API (Python/Lua), Fusion scripting, and workflow automation.

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自动驾驶 (Autonomous Driving) Master OS — automated mastery of Autonomous Driving: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on Autonomous Driving problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「自动驾驶」「智能驾驶」「智驾」「辅助驾驶」「领航辅助」

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。