家庭や小規模ラボのネットワーク変更前に、機器構成と復旧手順を整理するスキル。VLANによる分離、DNSフィルタリング、VPN導入を段階的に計画・点検します。
- 普段使う端末とIoT・来客端末の分離
- DNSフィルタリングへの移行計画
- VPNによる遠隔アクセスの見直し
2.1万 件 ・ 関連度順
概要と使いどころ
家庭や小規模ラボのネットワーク変更前に、機器構成と復旧手順を整理するスキル。VLANによる分離、DNSフィルタリング、VPN導入を段階的に計画・点検します。
技術や設計を選んだ理由を、背景・比較案・影響とともにMarkdownへ記録するスキル。連番と索引で整理し、既存の記録から過去の判断理由も確認します。
言語モデルに指示への応答や好ましい回答を学習させるため、TRLによる追加学習を案内するスキル。データ準備、学習方式の選択、報酬モデルの学習や評価を扱います。
メールやウェブサイト、ローカルファイルから進捗を集め、定期更新するダッシュボードを作成。要対応事項や変更履歴をまとめ、重要な変化があったときに通知します。
A three-card social-media carousel laid out as 1080×1080 squares — three cinematic, on-brand panels with display headlines that connect across the series ("onwards." → "to the next one." → "looking ahead."). Each card has a brand mark, a number / total, a caption, and a "loop" affordance. Use when the brief asks for a "carousel post", "social carousel", "Instagram carousel", "LinkedIn series", "X thread cards", or "三连发".
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。
Kanban / task board with columns (To do / In progress / In review / Done), draggable-looking cards, assignee avatars, swimlanes, and a top filter bar. Use when the brief mentions "kanban", "task board", "sprint board", "trello", "看板".
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。
Operates Fictiv (app.fictiv.com), the on-demand manufacturing platform, end to end in the user's browser. Covers uploading CAD parts, configuring process, material, finish, threads, tolerances and inspections, getting instant or manual quotes, reading and fixing DFM feedback, choosing lead time and region, checking out and paying (card or PO), tracking orders, reordering, and troubleshooting. Applies when the user mentions Fictiv, wants a part CNC machined, 3D printed, sheet-metal fabricated, urethane cast, injection or compression molded, or die cast through an online service, asks to "get a quote" or "order parts" for a STEP/SLDPRT/STL file, wants to check a Fictiv quote or order status, or has a problem with a Fictiv upload, DFM warning, price or checkout. Also applies when the user wants custom parts manufactured and has a Fictiv account, even if Fictiv is not named.
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。
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
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。
Binance Onchain Pay enables users to buy cryptocurrency with fiat (e.g., EUR, USD) or send existing crypto from their Binance account directly to any external on-chain wallet address in a single flow—no manual withdrawal needed. Enables partners to integrate crypto buying services: - payment-method-list: Get available payment methods (Card, P2P, Google Pay, Apple Pay, etc.) with limits for a fiat/crypto pair - trading-pairs: List all supported fiat currencies and cryptocurrencies - estimated-quote: Get real-time price quote including exchange rate, fees, and estimated crypto amount - pre-order: Create a buy order and get redirect URL to Binance payment flow - order: Query order status and details (processing, completed, failed, etc.) - crypto-network: Get supported blockchain networks with withdraw fees and limits - p2p/trading-pairs: List P2P-specific trading pairs
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。
Triage open herdr GitHub issues into a concise decision-first Markdown table. Use when the user says "triage", asks to triage open issues, asks which issues need attention, or wants issue priority/recommendation lights for herdr.
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。
Converts Word (.docx) documents into Markdown so their contents can be accurately analyzed, summarized, searched, or extracted from. Use this skill whenever the user shares, references, or asks about a .docx file — even if they don't say "convert" or "markdown" explicitly. This includes requests to "read", "summarize", "review", "extract data from", "compare", or "analyze" a Word document, resume, report, contract, or proposal. Always run the bundled conversion script to produce Markdown first; do not attempt to parse .docx content directly or write ad-hoc conversion code. Also use this skill for batch requests involving a whole folder of Word documents. IMPORTANT: When the user references a folder or set of documents containing multiple file types (.pdf, .docx, .xlsx), invoke ALL three sibling skills — convert-pdf-to-md, convert-word-to-md, and convert-excel-to-md — so no file type is silently skipped.
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。
Work through tasks on a kanban board stored in OpenViking (viking://agent/kanban/<board>/, one markdown file per task). Use when the user says "ov kanban", "kanban", "看板", asks to put a task on the board, hand off the current work, continue a task another agent started, or run an unattended task loop. A board holds many tasks; each task file is the handoff itself - a frontmatter header (id, status, owner, board) plus Goal, Context, Decisions, Progress, Next, Questions, Log - and its process detail is folded into an archive file instead of being summarized away, so any agent with the `ov` CLI can resume it and drill down when needed.
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。
当用户需要创建、读取、编辑或处理 Word 文档(.docx)时,使用此技能。触发场景包括提到“Word 文档”、“.docx”,或要求生成带目录、标题、页码、信头等格式的专业文档;也包括提取或重组 .docx 内容、插入或替换图片、在 Word 文件中查找替换、处理修订或批注,以及将内容整理为正式 Word 文档。如果用户要求生成“报告”“备忘录”“信函”“模板”等 Word / .docx 交付物,也应使用此技能。不要用于 PDF、电子表格、Google Docs,或与文档生成无关的一般编程任务。
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。
Turns what is actually selling into a reorder decision and gets it all the way into the books — computes sales velocity and conservative stockout dates per item, sizes the reorder, drafts the purchase order and the vendor email, and then stages the matching entry so the bill matches against the PO when it arrives. Flags the money sitting still too, so dead stock gets cleared instead of reordered. Runs on Shopify, Square, or an uploaded sales and stock CSV, and deepens with QuickBooks, Gmail or M365, Calendar, and NetSuite. No PO is sent and no vendor is emailed without approval. Use it when the owner says "what do I need to reorder," "am I going to run out," "restock," "we keep running out of filters," "draft a PO for my supplier," or "how much cash is sitting in the warehouse."
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 building a Kubernetes Operator — custom controllers that reconcile CRD state. Triggers on "build an operator", "CRD design", "reconcile loop", "controller-runtime", "kubebuilder", "operator-sdk", "metacontroller", "KOPF", "operator capability levels", or "custom resource". Ships CRD validator, reconcile-loop linter, and OperatorHub capability auditor (all stdlib Python), 4 references on the operator pattern + CRD design + reconcile patterns + tooling landscape, and a /operator-audit slash command. NOT a generic k8s skill — specifically the Operator pattern.
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。
Generate a Product Requirements Document (PRD) for a new feature. Use when planning a feature, starting a new project, or when asked to create a PRD. Triggers on: create a prd, write prd for, plan this feature, requirements for, spec out.
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。
Convert PRDs to prd.json format for the Ralph autonomous agent system. Use when you have an existing PRD and need to convert it to Ralph's JSON format. Triggers on: convert this prd, turn this into ralph format, create prd.json from this, ralph json.
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。
URDF robot description authoring and validation. Use when creating, editing, inspecting, validating, or debugging `.urdf` files, robot links, joints, limits, inertials, visual/collision geometry, mesh references, frame conventions, or robot-description artifacts. Use the SRDF skill for MoveIt2 semantic groups and IK/path-planning semantics; use the CAD skill for STEP/STL/3MF/DXF/GLB outputs. Open and visually review existing URDF files in CAD Viewer.
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。
Runs a route through ScenarioRunner's RouteScenario mode (--route / --route-id) with an autonomous agent driving the ego — the same mechanism the CARLA Leaderboard uses, and the only way to reach the ~34 route-only scenario classes (Accident, ParkedObstacle, HazardAtSideLane, InvadingTurn, HardBreakRoute, YieldToEmergencyVehicle, junction and actor-flow scenarios). Inspects route files, lists route ids and their scenarios, and runs one or all of them. Use when the user asks to "run a route", "drive a route with my agent", "run leaderboard scenarios without the leaderboard", or names a route-only scenario type.
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。
Runs the CARLA Leaderboard evaluator over a set of routes with your agent — routes/routes-subset/repetitions/track selection, checkpoint and live-results endpoints, resume after a crash, recording, and the debug levels — for leaderboard 1.0, 2.0 or 2.1. Preflights the whole stack (version pairing, maps, ports, agent class, sensor budget) before spending hours, and hands the world back in async mode. Use when the user asks to "run the leaderboard", "evaluate my agent", "run routes_training", "resume an evaluation", or "reproduce my submission locally".
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。
Inspects a recorded CARLA .log without replaying it — show_recorder_file_info for the header/actors/frames, collision queries between actor categories, and blocked-actor queries for vehicles that got stuck. Use when the user asks to "what's in this recording", "show recorder info", "which vehicles collided", "find collisions in the log", or "which actors were blocked/stuck".
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。
Writes an autonomous agent for the CARLA Leaderboard — an AutonomousAgent subclass with setup/sensors/run_step/destroy, a sensor suite inside the track's budget, and the right constructor signature for the leaderboard version (1.0 and 2.x differ). Generates a working skeleton, validates the sensor configuration against the real per-track limits offline, and covers the ROS1/ROS2 agent base classes. Use when the user asks to "write a leaderboard agent", "make my agent work with the leaderboard", "add sensors to my agent", "port my agent to 2.1", or hits SensorConfigurationInvalid.
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。
Reads a CARLA Leaderboard results.json — per-route driving score, route completion, infraction penalty and the infraction lists — explains how the score was computed for that leaderboard version, and rescores an existing result under the other version's rules (2.0 multiplicative vs 2.1 additive) without re-running anything. Also diffs two runs and merges sharded result files. Use when the user asks "what did I score", "why is my score low", "did my agent pass", "why don't my scores match the leaderboard", or hands over a results.json.
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。
Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.
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。