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概要と使いどころ
Marketing budget planning and forecasting — channel allocation, CAC targets, ROI projections, and spend optimization. Use when "marketing budget", "budget planning", "channel allocation", "marketing spend", "CAC forecast", "budget forecast", "how much should I spend", "allocate budget", or any request to plan, forecast, or optimize marketing spend.
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。
Deterministic workflow to find and export full podcast transcripts as cleaned TXT files from YouTube URLs, episode webpages (including Xiaoyuzhou), Apple Podcasts title search, X/Twitter links, direct audio URLs, or plain episode titles. Use when users ask for 逐字稿/文字版/transcript/txt and want minimal trial-and-error.
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。
Forecast infrastructure and application metrics using Prophet or statsmodels for capacity planning, cost optimization, and proactive scaling. Visualize predictions in Grafana and set up alerts for projected resource exhaustion. Use when forecasting infrastructure capacity needs for CPU, memory, or disk, planning hardware procurement for next quarter, predicting cost trends to optimize cloud spending, or setting up proactive scaling policies based on predicted load.
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 ARIMA models for time series forecasting with trend and seasonality decomposition. Use this skill when the user needs to forecast future values from historical sequential data, test for stationarity, or select ARIMA parameters — even if they say 'time series forecast', 'predict next month sales', or 'ARIMA model'.".
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 gives a topic and wants an automated topic-driven narrated explainer, podcast, or knowledge-summary video (Bilibili / YouTube / Xiaohongshu / Douyin / WeChat Channels), or asks to learn visual design patterns from a reference video/image. Trigger when the user mentions creating a knowledge video, narrated explainer, video podcast, or animated infographic-style video from a topic — even if they don't say "video podcast" explicitly. Also trigger when the user wants to regenerate, re-render, rebuild, update, or iterate on a narrated video this skill already produced — e.g. they edited the script/prompt, changed the visuals, or swapped the background music and want the final video remade (reuse the existing videos/{name}/ directory, never start a new project). Do NOT trigger for generic video editing, trimming, format conversion, color grading, or non-narrative video tasks. Produces 4K video via research → script → TTS → Remotion → MP4 + BGM.
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。
Revenue Intelligence setup: activating the RI app and its CRM Analytics assets, Einstein deal insights, the opportunity-change waterfall, and forecast-accuracy analytics for sales leaders. NOT for configuring the Pipeline Inspection view, its metrics and review cadence - use admin/pipeline-review-design. NOT for forecast types, categories, rollups and quotas - use admin/collaborative-forecasts.
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。
View, create, cancel, bid, and claim Aavegotchi GBM auctions on Base mainnet (8453). Subgraph-first discovery (Goldsky), with onchain verification + execution via Foundry cast. Safety-first: DRY_RUN defaults to 1 (simulate with cast call; only broadcast with cast send when DRY_RUN=0 and explicitly instructed).
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 working with Cast Ai — cAST AI Kubernetes cluster optimization and cost management. Covers cluster cost optimization, spot instance management, cost reports, node rebalancing, security posture, and workload right-sizing. Use when optimizing Kubernetes cluster costs, managing node lifecycle, or analyzing cloud spend with CAST AI.
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。
都市名や空港コード、座標を指定して、現在の天気や予報を調べます。気温、体感温度、降水量、風などを要約し、外出前の確認や旅行の計画に使えます。
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
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 help with public relations, earned media, press coverage, journalist outreach, or media strategy (not pull requests). Also use when the user mentions 'PR,' 'press,' 'press release,' 'media outreach,' 'pitch a journalist,' 'get featured,' 'media list,' 'media kit,' 'press kit,' 'newsjacking,' 'news hijack,' 'HARO,' 'Qwoted,' 'Featured,' 'reporter request,' 'tech press,' 'TechCrunch,' 'thought leadership placement,' 'op-ed,' 'guest article,' 'press contacts,' 'podcast prep,' 'podcast guest,' 'prep me for this podcast,' 'how do I get press,' 'PR crisis,' 'crisis communications,' 'respond to backlash,' 'we got hacked,' 'data breach statement,' or 'holding statement.' Also covers crisis response when something goes wrong. For startup/SaaS/AI directory submissions, see directory-submissions. For product launches, see launch. For social-media engagement, see social. For cold-email outreach to prospects, see cold-email.
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。
Performs zero-shot time-series forecasting with Google's TimesFM, including regular-grid CSV preparation, quantile forecasts, XReg covariates, and held-out evaluation. Uses the Apache-licensed TimesFM 2.5 checkpoint by default and documents the distinct TimesFM 3.0 multivariate API and weight-license requirements.
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。
Supports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.
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。
Install and use the official AI Podcast Voiceover package, pinned by digest, for paid hosted work on the Beatra service.
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。
Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization. Use when analyzing sales pipeline coverage, forecasting revenue, evaluating go-to-market performance, reviewing sales metrics, assessing pipeline analysis, tracking forecast accuracy with MAPE, calculating GTM efficiency, or measuring sales efficiency and unit economics for SaaS teams.
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。
Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.
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。
Create and validate Earth2Studio data source wrappers (DataSource, ForecastSource, DataFrameSource, ForecastFrameSource) from remote stores. Do NOT use for fetching data with existing sources, model inference, or installation tasks.
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 deterministic forecast scripts with Earth2Studio (model, data source, IO, inference). Do NOT use for ensemble, diagnostics, data-only fetch, or install.
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。
Forecast Azure spend and price planned resources or workloads. WHEN: "forecast Azure spending", "project next month cost", "compare forecast to my planning target", "how much will Azure cost", "estimate VM cost", "compare storage tiers", "compare Azure regions", "retail price", "EA rate card", "negotiated pricesheet". DO NOT USE FOR: configured budget health or alerts, bill analysis, cost spikes, rightsizing, or commitments.
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 AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.
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。
How to produce a demand forecast for a SKU, and when to delegate that to a subagent vs. compute it yourself. Load this for any task involving "forecast", "how much will we sell", "next month", promos, or seasonal SKUs.
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。
Forecast Azure spend and price planned resources or workloads. WHEN: "forecast Azure spending", "project next month cost", "compare forecast to my planning target", "how much will Azure cost", "estimate VM cost", "compare storage tiers", "compare Azure regions", "retail price", "EA rate card", "negotiated pricesheet". DO NOT USE FOR: configured budget health or alerts, bill analysis, cost spikes, rightsizing, or commitments.
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 Godot 4.7 physics bodies and detection in 2D and 3D: RigidBody, StaticBody, Area, and CharacterBody; collision layers vs masks; contact/overlap signals; and raycasts (RayCast nodes and direct space-state queries). Use when configuring collision layers/masks, detecting overlaps with Area2D/Area3D, applying forces to a RigidBody, or casting rays in a Godot project (.tscn with physics bodies), including 3D projects running Jolt Physics, the default 3D engine for projects created in 4.6+.
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。
Read and write Kit (ConvertKit): list subscribers, broadcasts, sequences, tags; draft broadcasts. Trigger phrases: kit, convertkit, newsletter, broadcasts, subscribers.
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。