413 件 ・ 関連度順
概要と使いどころ
ElevenLabs: check subscription usage, list voices, and generate text-to-speech audio. TTS spends quota and needs --confirm. Trigger phrases: elevenlabs, eleven labs, voice api, tts, text to speech.
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。
Puts a built website live on a free HTTPS link, or your own .com with no DNS. Use when the user says "put it online", "go live", "make it live", "put this live", "publish my site", "share it with friends", "send my friends a link", "get a link", "make it public", "it only works on localhost" or "get a .com", or asks to deploy or host a site built with an AI tool (Claude Code, Cursor, Codex, Windsurf, Lovable, Bolt, v0, ChatGPT), or mentions DropTheHassle, and has not picked another host. Covers building first, CLI or MCP setup, deploying, the claim link, the live check, linking a server part the user hosts on AWS, Google Cloud, DigitalOcean or their own server with set_backend, and domain search. The agent never spends money. The human pays.
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。
Assemble a 3D-CGI app sizzle — nano-banana CGI plates (blank-glow floating phone + a CGI studio with rim-light + placeholder burst shapes; studio look and phone finish come from the recipe choices) plus PIL compositing of the REAL App Store screenshots onto the bezel + burst-out overlays, driven by Kling 3.0 i2v steady-float per beat with a per-beat Ken-Burns FFmpeg push-in fallback when Kling garbles the UI, then VO/music mix (sidechain duck, loudnorm) + 1.15x speed + anti-AI grain finalize. The on-screen UI, any faces in it, and the wordmark are ALWAYS real assets composited via PIL — never AI-rendered. The paid steps (plates, i2v clips, VO, music) are separate capabilities; this ships the config + PIPELINE + FREE assembly and the recipe orchestrates the spend. Use for the cgi-app-sizzle video format.
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。
Answer questions about a brand's Meta ads (spend, results, which ad is winning, is it paused, why did Goose do that) only from reads made in the same turn, with the data window and sync time on every number and a plain caveat when the connection is stale or partial. Use it whenever a user asks how their ads are doing or why an ad action was taken.
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。
Scrape competitor ads from Meta's Ad Library (Facebook, Instagram, Messenger, Threads, WhatsApp). Search by company name, Facebook Page URL, or keyword. Returns ad creatives, spend estimates, reach, impressions, and campaign details. Use for competitive ad research, messaging analysis, and creative inspiration.
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。
Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.
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。
Reduce AWS spend with rightsizing, autoscaling, commitment planning, and storage lifecycle policies. Use when running FinOps reviews, lowering cloud bills, or improving cost-per-request metrics.
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。
Reduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and self-hosting strategies. Track spend by team and model, set budgets, and implement cost-aware routing.
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。
Supply Chain Bottleneck Analyzer for Walmart Marketplace sellers. Diagnose cash flow, inventory, WFS costs, and referral fees. Includes comparison with Amazon FBA, lower storage fee optimization, and Walmart Connect ad spend analysis. No API key required for basic analysis.
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。
Supply Chain Bottleneck Analyzer for Shopify/DTC stores. Diagnose cash flow, inventory, shipping costs, and customer acquisition efficiency. Includes CAC/LTV analysis, 3PL cost optimization, and ad spend benchmarks. No API key required for basic analysis.
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。
Shopify/DTC profit margin calculator for sellers. Calculate cost breakdowns including ad spend, CAC, payment processing fees, and 3PL costs. Includes LTV/CAC analysis and DTC-specific benchmarks. No API key required.
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 after any web or API search, before opening results or spending another round. Jev picks which results to read, whether the evidence is enough, and which query to run next from ones you wrote.
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。
Produce a scoped CCAM cost and token report by model, provider, source, and session. Use for spend reviews, model-mix analysis, unpriced usage detection, or export-friendly cost summaries.
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。
Roll up Claude Code sessions by working directory (project) from Agent Monitor data — session count, total cost, total tokens, and last-active timestamp per cwd — so per-project activity can be compared at a glance. Use when summarizing where effort and spend went across projects.
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。
Estimate the dollars saved by routing eligible Claude Code work to a cheaper model family, using the Agent Monitor pricing engine. Re-prices each model's token mix at the target family's rates and quantifies the delta. Uses /api/pricing (rates), /api/pricing/cost (current per-model spend), /api/sessions, and /api/analytics. Use when hunting for cost cuts or comparing model tiers.
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 the configured cost alert rules and the alerts currently fired on the Agent Monitor dashboard, then explain exactly what tripped and why. Uses /api/alerts (fired feed) and /api/alerts/rules (definitions). Use when checking spend alerts or asking why a cost alarm went off.
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。
Break down Claude Code costs using the Agent Monitor pricing engine. Shows per-model costs (input, output, cache_read, cache_write at $/Mtok rates), per-session costs, daily trends, and compaction baseline token recovery. Use when analyzing spending, comparing model costs, or planning budgets.
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。
Audit an agent's context layout against the four places: system prompt, tools, history, tail. Use when the user asks to audit, review or fix their agent's context, prompt caching, token spend per turn, or CLAUDE.md / AGENTS.md layout. Read-only: reports findings and a fix list, changes nothing. Do NOT use for writing evals (evals-bootstrap) or for loop design (goal-test).
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 the user wants to plan paid ads strategy, allocate ad budget, or choose paid channels. Also use when the user mentions "paid ads," "paid media," "PPC," "SEM," "web ads," "app ads," "TV ads," "CTV," "OOH," "banner ads," "ad network," "ad alliance," "Taaft ads," "Shopify App Store ads," "Google Ads," "Meta Ads," "PMF testing," "PMF validation," "test product-market fit with ads," "ad spend," "ad budget," "ROAS," "paid acquisition," "Quality Score," or "ad-to-page alignment." For Google Ads execution, use google-ads. For Meta Ads execution, use meta-ads. For landing page alignment, use landing-page-generator.
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。
Guide and execute the migration of asynchronous code from RxJava to Kotlin Coroutines and Flow. Use this skill when a user asks to convert RxJava (Observables, Singles, Completables, Subjects) to Coroutines (suspend functions, Flows, StateFlows).
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。
Vendor lifecycle — weighted selection scorecards, risk tiering, renewal and notice-deadline tracking, spend concentration, and SLA credits. Use when selecting a vendor, preparing a renewal, or reviewing a vendor portfolio.
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。
Audit the martech stack for gaps, overlaps and wasted spend, with a consolidation plan. "audit our martech stack"
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。
Show status of every tracked campaign: health, spend, executions, pending approvals. "what campaigns are running right now"
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。
Creates an Agent Authority Charter for enterprise or regulated AI agents before deployment. Use this Skill when a user needs to define what an AI agent is allowed to do, who delegated authority to it, what actions are permitted or prohibited, when human approval is required, what evidence must be preserved, and how the agent can be suspended, revoked, or escalated.
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。