「live」の検索結果

When you paste raw human input — a call transcript (Grain, Zoom, Granola, Fathom), a text or email from a client/partner/friend, a voice-memo dump, or meeting notes — and want it converted into structured work. Extracts decisions, action items (yours vs theirs), bugs/feature requests, and facts worth keeping; files GitHub issues in the right repo, captures to the second-brain vault, and drafts (never sends) the reply. Triggers on "/ingest", "ingest this", "here's my call with X," "here's the transcript," "this is from [person]," "[person] asked me this," "from [person]:", a pasted transcript with speaker labels, or a forwarded client message that clearly expects processing. Person→project routing lives in a private config; unknown senders get asked about once, then remembered.

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。

When you want to brainstorm and check available .com domains for a new project — brand naming, aftermarket pricing (HugeDomains / Afternic / Sedo / Dan), USPTO trademark screening, and social handle availability. Built on Laura Roeder's "work backwards from availability" method. Combines Vercel CLI, whois, Domainr, Namecheap, and agent-browser, each for what it reliably does. Workflow: budget → brainstorm → availability check → whois cross-check → price → aftermarket sweep (plus liveness probe and drop-watch) → bucket → negotiate → trademark + socials → buy. Triggers on "/domain," "find a domain," "check domain availability," "brainstorm a domain," "what .com is available for X," "domain hunt," "name my project," "is X.com available," "aftermarket price on X.com," "trademark check for X."

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。

When you want multiple expert perspectives on a founder/operator question — a simulated board of advisors (Jason Fried, Elon Musk, Jeff Bezos, Jensen Huang, Bob Iger, Paul Graham, Naval Ravikant, Sara Blakely). Bring a real decision — "should I raise prices?", "hire my first employee?", "raise or bootstrap?", "kill this project?" — and the council weighs in through documented frameworks, surfaces disagreements, and synthesizes a recommendation. Also use for 'maker council,' 'board of advisors,' 'what would Bezos do,' 'what would Jason Fried say,' 'channel Naval,' 'ask the council,' or how a famous founder would approach a problem. Optional live-research pass via deep-research / watch-video / last30days. Marketing questions go to marketing-skills' marketing-council. Archives to ~/.config/makerskills/maker-council/archive/. To commit to a direction, hand off to decide.

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 auditing or recalibrating game balance: build a source-driven Monte Carlo balance lab (Rust + rayon) that extracts live game data, simulates human playstyles (AFK→pro), emits win-rate/economy verdicts with confidence intervals, and bruteforce-tunes parameters. Trigger on unfair levels, unreachable shops, farm exploits, interest-curve cliffs, post-content recalibration, or CI balance JSON diffs. Keywords: balance lab, Monte Carlo, win rate, difficulty curve, economy career, playstyle simulation, Resource extraction, GDScript parser, bruteforce tuning.

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。

Route a Bevy 0.20 race. Use when lap and gate index live on the racer, the race clock is one resource, and gate checks run after the clock step in one chain. Keywords: Bevy, Racing, Racer, RaceClock, FixedUpdate, chain, genre.

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 native WebMCP tools to edit the project open in Timeline Studio. Inspect clips and available assets, preview and apply multi-track, caption style/position and project framing edits; sample rendered media; run local voiceover, transcription, relighting analysis and depth-video jobs; insert media; undo; save; or export video with progress and cancellation. Use for the live browser editor, not local project-file editing.

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 auditing or recalibrating game balance: build a source-driven Monte Carlo balance lab (Rust + rayon) that extracts live game data, simulates human playstyles (AFK→pro), emits win-rate/economy verdicts with confidence intervals, and bruteforce-tunes parameters. Trigger on unfair levels, unreachable shops, farm exploits, interest-curve cliffs, post-content recalibration, or CI balance JSON diffs. Keywords: balance lab, Monte Carlo, win rate, difficulty curve, economy career, playstyle simulation, Resource extraction, GDScript parser, bruteforce tuning.

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。

Generic PowerPoint authoring skill for A-share investment analysis and pitch decks. Creates professional 路演PPT / 投资分析PPT for any A-share company using live data from iFind MCP (Tier-1) and AkShare MCP (Tier-2 fallback) tools. All company-specific values are parameterized — never hardcoded. Triggers on "A股PPT制作", "投资PPT", "制作PPT", "路演PPT", "pitch deck", "PowerPoint [company/ticker]", or any request to create slides for a Chinese stock. When invoked, use the `generate_a_share_ppt` script with --company and --ticker args.

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 the user wants to learn Godot while building — teaching mode that explains the concept, the editor setup, and what to verify, instead of just delivering code. Triggers on "teach me", "explain as we go", "I'm learning Godot", "guide me", "walk me through", "help me understand".

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。

Your launch lead. Builds a dated, step-by-step launch plan: a cheap real-world test first (a waitlist, a pre-sale or a pop-up with a real price, so real buyers confirm what the simulated panel said), then the countdown to opening day with owners and deadlines, the launch-day run sheet, and the first 30 days of what to measure and what to change. Use when the user says "how do I launch", "launch plan", "when can I open", "launch checklist", "go live", or "soft open".

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。

Builds an offer too good to refuse. Lists every problem the buyer hits on the way to the result they want, turns each into a solution, trims to what is cheap to deliver and valuable to the buyer, and stacks it with honest bonuses, a guarantee the CFO can afford, real urgency and a clear name. Scores it on the value equation (outcome, likelihood, time, effort) and re-tests it on a quick buyer panel. Use when the user says "make my offer better", "why won't people buy", "what should I include", "guarantee", "bonuses", "grand slam offer", or after the panel shows people passing.

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。

Lay out and organize a ComfyUI workflow cleanly on the live panel canvas. Dependency-layered node placement with no overlaps, subgraphs, colored group boxes, and subgraph rail alignment. Use when asked to tidy / clean up / organize / arrange a workflow, add groups or subgraphs, fix overlapping nodes, or build a workflow that should look good from the start.

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。

Write architecture fitness functions — deterministic tests that enforce a project's hard rules (module boundaries, offline guarantees, content contracts) from inside its own test target. Use when a constraint lives only in prose (CLAUDE.md, code review) and should become un-arguable.

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。

AlarmKit integration for scheduling alarms and timers with custom UI, Live Activities, and snooze support. Use when implementing alarm or timer features in iOS 26+ apps.

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, install, launch, and screenshot an iOS app in the Simulator to verify a change visually. Use when the user wants to run the app, see a change live, screenshot the running app, or confirm a UI fix actually works (not just that it compiles).

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。

Close the post-launch loop — turn a live app's App Store signals (reviews, analytics, sales, crashes, listing conversion) into a metric-tagged backlog for the next version, AND verify whether last cycle's changes moved the metric they promised to move. Read-only on App Store Connect; every change is surfaced and routed to another command, never auto-applied. Use before planning the next version, on a monthly cadence, or ~1-2 weeks after shipping to check if a change worked.

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。

Genomic data analyses requires integrated visualization of known genomic information and new experimental data. Gviz uses the biomaRt and the rtracklayer packages to perform live annotation queries to Ensembl and UCSC and translates this to

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。

Expert knowledge for Azure AI Video Indexer development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring live camera analysis, custom AI insights, OpenAI summaries, Video Indexer APIs, or face redaction, and other Azure AI Video Indexer related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI Search (use azure-cognitive-search).

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。

Expert knowledge for Microsoft Foundry Local (aka Azure AI Foundry Local) development including best practices, decision making, configuration, and integrations & coding patterns. Use when compiling HF models with Olive, using Foundry Local CLI, embeddings/chat/audio APIs, or OpenAI-style integrations, and other Microsoft Foundry Local related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Azure Local (use azure-local), Azure Content Understanding in Foundry Tools (use azure-content-understanding).

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。

Expert knowledge for Azure Speech in Foundry Tools development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using STT/TTS, custom voice or avatars, Speech containers, Voice Live, or telephony/WebRTC streaming, and other Azure Speech in Foundry Tools related development tasks. Not for Azure Content Understanding in Foundry Tools (use azure-content-understanding), Azure AI Vision (use azure-ai-vision), Azure AI Video Indexer (use azure-video-indexer), Azure Translator (use azure-translator).

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。

Expert knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns. Use when using Face detection, identification, verification, liveness, PersonGroup/Directory, or Face API quotas, and other Azure AI Face related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use azure-document-intelligence).

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。

Expert knowledge for Azure Event Grid development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring Event Grid/MQTT namespaces, securing endpoints, routing events, integrating Functions/Service Bus, or troubleshooting delivery, and other Azure Event Grid related development tasks. Not for Azure Event Hubs (use azure-event-hubs), Azure Service Bus (use azure-service-bus), Azure Notification Hubs (use azure-notification-hubs), Azure Web PubSub (use azure-web-pubsub).

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。

Deep security audit of a smart-contract repo OR a live on-chain contract by address - detect Solidity, model the protocol invariants and trust boundaries first, run Slither (best-effort) plus a bounded agentic pass that hunts for a path breaking each invariant, triage, adversarially verify, prove with a fuzzer, and drive each finding through the shared responsible-disclosure routing. The dedicated contract arm split out of vuln-scanner.

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。

Render a short (~10s) video on any topic with Remotion - the agent writes a storyboard JSON, a bundled React/Remotion project renders it to an MP4, and the clip is committed to the repo and delivered by URL. No editor, no external generative API.

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。