「live」の検索結果

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。

Turn a repo, product page, or update into a recording-ready video script in a receipts-first format - verifies every claim against live sources, then writes timestamped VO + on-screen direction with a plain-language glossary, assets checklist, anti-tells, and a verify-before-recording list

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。

Token unlock and vesting tracker - quantify supply pressure via absorption ratio, classify cliff vs linear, and deliver one-line market reads

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。

Generate a small app or tool and deploy it live to Vercel via 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。

Live-data research via the glim.sh MCP - web search, full page extraction, X/Twitter, Reddit, GitHub, Amazon, and YouTube transcripts - synthesized into a cited digest. Pay-per-call from the connected account balance; OAuth Connect via the dashboard MCP panel.

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。

Autonomous compute-reselling agent on Surplus Intelligence - resells free or low-cost provider compute across Bankr, AWS Bedrock, and Google Vertex (GCP) as one skill. Reads the live market + your cost + your usage, auto-lists your models per enabled provider, and reactively prices each offer to win routing within a cost floor, cap, and health guardrails.

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 Trellis channel for live multi-agent collaboration, spawned workers, cross-agent review, progress inspection, forum channels, and channel log debugging.

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。

Expand a hard-to-build niche list from ~10 known-good seed companies into a full qualified TAM. Seed fingerprinting (how do good-fit companies ACTUALLY show up in the company database's filters) → lookalike generation (Prospeo company_lookalike, Exa findSimilar, Parallel.ai entity search) → filter mining with a precision/volume scorecard → wide pull with auto-sharding → cheap-AI qualification → live-website verification → client transparency report. Use when a vertical list feels "too small" (medical groups, hedge funds, Medicare brokerages), when known good-fit companies don't show up in keyword searches, or when someone says "expand this list", "the TAM should be bigger", "find more companies like these".

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。

Autonomous cold email campaign launcher. Takes one target company domain, scrapes their website, generates an ICP with Claude, pulls matching leads via Prospeo, enriches emails + company descriptions, personalizes each lead with parallel Claude Code Task sub-agents (A/B/C variants), and uploads as a live Smartlead campaign. Uses local JSON files for state (no database required). Use for automated daily campaign launches after you have an initial `client-profile.yaml` from /icp-onboarding. Triggers on "auto-research", "launch an automated campaign", "daily campaign", "run the research loop".

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。

Upload a CSV of leads + a variants YAML (produced by /campaign-copywriting) to Smartlead as a DRAFT campaign. Handles tag-scoped inbox selection, A/B/C variant assembly, custom field mapping, schedule config, and batch lead upload. ALWAYS creates in DRAFT — you review in Smartlead UI and hit Start manually. Use after /campaign-copywriting, just before the campaign goes live.

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。

Operational playbook for running cold email continuously. Prescribes what to do on Monday / Wednesday / Friday / biweekly / monthly / quarterly. Use this as your ongoing cadence once your first campaign is live. What separates hobbyist from top 1% operators isn't tooling — it's consistency. This skill is the schedule.

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。

Decides which named technologies a company actually runs on its website, verified against the live site. Triggers on "find companies using Shopify", "they're on HubSpot", "tech stack targeting", "technographics", "who uses Klaviyo", "companies running WordPress". Outputs a per-domain verdict (tech_confirmed plus the verified stack and its evidence); the copy-ready clause is OFF by default and runs only when the operator asks for one.

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。

META skill — build the largest possible qualified lead list for any request, end to end. Orchestrates discovery (Prospeo + GetLeads + Blitz + Google Maps + lookalike snowball from /list-expander), AI qualification with live-website verify, uncapped contact pull (GetLeads → Blitz → Prospeo), and provider emails (GetLeads/Blitz/Prospeo) validated with MillionVerifier before sending. Use for any "build me a list", "get me leads for X", "find everyone who...", client list request, or campaign list build. Starts with a 7-line intake brief; outputs to Postgres, Google Sheet, and/or CSV (asks which).

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。

Converges an underspecified request into an IntentSpec: looks up what sources answer, asks only what they cannot, halts instead of guessing, checks delivery against the spec. Use when a request to implement, add, change, fix or configure leaves a decision open — scope, approach, failure behaviour, what done means — contradicts itself, reads two ways, or rests on a premise sources rule out. Silent on a fully stated request its sources do not contradict; not for explaining existing state.

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 an influencer marketing strategy — finding influencers, briefing, contracts, deliverables, performance tracking, micro vs macro strategy, outreach, and FTC compliance. Use when the user says "influencer marketing", "influencer strategy", "work with influencers", "influencer outreach", "influencer brief", "find influencers", "micro influencer", "macro influencer", "nano influencer", "creator marketing", "brand ambassador", "influencer campaign", "influencer collaboration", "seed influencers", "gifting influencers", "paid influencer", "influencer ROI", or wants to use influencers or creators to grow the brand.

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。

Define KPIs, metrics, and tracking systems to measure brand health, awareness, perception, and equity over time. Use when the user says "brand measurement", "brand metrics", "how do we measure the brand", "brand KPIs", "brand health tracking", "brand awareness metrics", "brand equity measurement", "is our brand working", "brand ROI", "brand performance", "brand tracking", "brand health score", "prove brand value", "brand dashboard", or needs to show stakeholders whether brand investment is delivering results.

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。

Review a diff against the goal spec assuming the code is BROKEN. The reviewer that lives in the maker's head always agrees with itself — this pulls review into a hostile, separate pass. Invoke after every code change before marking work done.

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 mentions GPT Image 2.0 or GPT Image 2.5, gpt-image-2, gpt-image-2.5, gpt_image_2_5, GPT-Image-2 prompts, the Flare / Sunburst variants, a transparent-background image, or wants to generate an image with GPT Image 2.0 or 2.5. Covers when to prefer GPT Image 2.5 over 2.0 (transparent background, xhigh/max quality, extra aspect ratios — from platform and OpenAI facts), the CLI-vs-MCP disagreement on gpt_image_2, the three-format prompt taxonomy (Format A structured JSON for UI mockups and layout-dense images; Format B dense cinematic prose for single-subject scenes; Format C auto-derive meta-prompt for theme-only concepts), per-format craft patterns, output conventions, the 6-item pre-delivery checklist, and cross-surface workflow context (companion static-ads-workflow.md for ad recreation; higgsfield-marketing-studio cross-surface-workflow.md §3 for ms_image / DTC Ads Higgsfield-native alternative).

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 mentions Higgsfield Canvas, a node-based or node graph workspace, an infinite board/canvas, chaining generations into a pipeline, or wants to wire prompts → images → videos across models on one surface. Covers what Canvas is, the node categories, the seven models that run inside Canvas, the named canvas patterns (Simple Seedance, Extend Video, Image Edit, StoryBoard With Elements, Long Video fan-out), the build-free / generate-paid cost model, reusable templates, assets-as-nodes, and Shared Canvas live collaboration. Also trigger on 'Higgsfield ComfyUI alternative', 'node workflow', or 'connect nodes to build a scene/campaign'.

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。