Convert technical plans into actionable development tasks with dependency graphs, effort estimates, and parallelization opportunities.
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。
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概要と使いどころ
Convert technical plans into actionable development tasks with dependency graphs, effort estimates, and parallelization opportunities.
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 driving/taxi duration, distance, and rough cost between two cities using the bundled distance matrix CSV. Use this skill when comparing ground travel options or validating itinerary legs.
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 camera motion with optical flow + affine/homography, allow multi-label per frame.
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。
Clause-by-clause contract risk analysis with severity scoring, financial exposure estimates, and prioritized remediation guidance
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。
This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.
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。
This skill should be used when the user asks to "calculate TAM", "determine SAM", "estimate SOM", "size the market", "calculate market opportunity", "what's the total addressable market", or requests market sizing analysis for a startup or business opportunity.
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。
Root-cause a failing or wrong empirical result with a disciplined reproduce → minimise → hypothesise → instrument → fix loop, instead of guessing-and-poking. Use when the user says "why is my regression wrong", "this number changed", "my script errors out", "the result won't reproduce", "debug this", "this estimate looks wrong", or "it worked yesterday". Tuned for research code (R/Stata/Python): type coercion, NA/merge blow-ups, factor levels, clustering/SE choices, weighting, collinearity/convergence, seeds, package-version drift. Use `--no-fix` to localize the root cause without editing shared or load-bearing files.
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 provisioning, setting a limit, or committing an estimate under uncertainty, size a buffer to residual error and the cost of breach—not to the optimistic edge.
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。
End-to-end orchestrator: from a business idea, app idea, or existing app to running Azure deployment with cost estimates and pre-deploy approval. Analyzes your app, auto-detects the right Azure services, scaffolds infrastructure code, and deploys — tailored to your app, not a template. Handles moving existing apps to Azure without rewriting or with minimal changes. WHEN: bring your app to Azure, plan my app, cost to run, is my code ready to deploy, deploy my app to the cloud, deploy all my services, what Azure services do I need, plan my Azure deployment, deploy my new app to Azure, one-click deploy, I have an app and want it on Azure, migrate my app to Azure, help me get started, build an app, no code yet, starter project. DO NOT USE FOR: use azd for deployment(use azure-deploy), optimizing existing costs (use cost-optimization), code readiness checks only (use azure-app-onboard-prereq).
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。
Azure VM/VMSS router. WHEN: create / provision / deploy / spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev/test, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus / compute_vm_list-images / compute_vm_check-quota.
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。
Analyze actual Azure spend, bill changes, and AKS or AI costs. WHEN: "Azure cost breakdown", "most expensive resources", "why did my bill increase", "cost spike", "unexpected charge", "Cosmos DB charges", "Foundry model costs", "AKS cluster cost", "namespace cost", "enable AKS cost analysis", "idle AKS capacity". DO NOT USE FOR: forecasts, pricing estimates, rightsizing, commitments, or 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。
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。
Optimize existing Azure resources and analyze Reservations or Savings Plans. WHEN: "optimize Azure costs", "reduce cloud spending", "rightsize resources", "find idle resources", "orphaned disk", "deleted VM still charged", "public IP still charging", "reservation utilization", "Savings Plan coverage", "commitment recommendation", "why is pay-as-you-go still charged". DO NOT USE FOR: cost spikes, forecasts, pricing estimates, budgets, or governance.
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。
Collects real financial data for any US publicly traded company from free public sources (yfinance) and outputs structured JSON for downstream skills (DCF modeling, comps analysis, earnings review): market data, historical financials, WACC inputs, analyst estimates — never fabricated fallback values. Use to collect or pull financial/market data, or gather DCF inputs, for a ticker.
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。
Pulls Bigdata.com (RavenPack) financial and news data via the official bigdata-client SDK and /v1/* REST endpoints — structured financials, prices, analyst estimates, entity-sentiment series, annotated chunk search, screener. Use when the Bigdata MCP's tearsheets/search feel thin and you need the machine-readable substrate: mentions of Bigdata.com, RavenPack, a bd_v2_ key, rp_entity_id, or chunk/query_unit cost.
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。
Fetches real, citable Bilibili (B站) video data — stats, metadata, tags, and full danmaku text — via login-free API calls, never hand-typed or estimated. Use when citing view/like/favorite counts, analyzing why a video performed, or archiving a Bilibili source into a knowledge base. Accepts BVID, av numbers, b23.tv links, or full URLs; subtitles and 收藏夹 (favorites) enumeration need the user's Bilibili login.
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 economic compensation (经济补偿金) when employment ends in mainland China: N, N+1 or 2N under the Labour Contract Law, with the high-earner cap, the part-year rule and the questions that decide which case applies. Use when asked 我被裁员了能拿多少补偿, N+1 怎么算, 经济补偿金计算, 违法解除 2N, or how much severance am I owed in China. Produces the scenario that likely applies and why, the calculation shown step by step, what to check before signing anything, and where to get it confirmed. Not legal advice.
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 asked 医保怎么报销, 异地就医怎么备案, 住院能报多少, 门诊报销比例, 手工报销要什么材料, 惠民保值不值得买, or work out what China's basic medical insurance (医保) will pay for a treatment. Produces the person's scheme (职工医保 or 居民医保), how a claim works for this case (direct settlement or manual reimbursement), an out-of-pocket estimate built from the city's own deductible, rate and cap, the cross-region registration (异地就医备案) steps, and the documents to keep.
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 asked 个体户怎么报税, 小规模纳税人增值税怎么算, 小微企业所得税优惠, 经营所得汇算, 开票超过免税额怎么办, or plan taxes for a sole trader (个体工商户) or small company in China. Produces the taxes that apply (增值税, 附加税费, 个人所得税经营所得 or 企业所得税), the relief that may apply with the announcement to check, a worked estimate from the person's own figures, a filing calendar, and the questions for the local tax office or 12366.
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。
Fit a retention curve to observed cohort data and project LTV — computed, not estimated. Use when someone has real cohort retention numbers (month 0, 1, 2…) and asks what lifetime value, lifetime periods, or long-run retention they imply, or whether retention is flattening or leaking. Produces a fitted power curve (parameters, R², retention floor), a 24-36 period projection, and a real .xlsx with live formulas where editing ARPU recalculates LTV — via the bundled zero-dependency script.
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 asked 积分落户怎么算, 我能不能落户上海 / 北京 / 深圳, 居转户条件, 落户积分差多少, 人才引进落户, or check eligibility for a city household registration (户口) in China. Produces the routes available in the person's city (积分落户, 居转户, 人才引进, 应届生落户 and others), a score estimate built only from the city's current official scoring table, the gap and how to close it, a document checklist and a timeline, each marked to confirm with the city's official notice.
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 structured churn analysis that separates avoidable from unavoidable churn. Use when investigating why customers are leaving, identifying at-risk segments, calculating net revenue retention, or building a retention intervention plan. Produces a churn report with rate calculations, categorised reasons by avoidability, segment breakdown, timing analysis, early warning signals, and prioritised interventions ranked by estimated impact.
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。
Plan a board game night that actually lands — the right games for your group size, mix, and time, in a running order that keeps energy up. Use when asked to plan a game night, what board game should we play, games for [N] people, or what to play with a mixed group. Produces game picks matched to player count and experience, a warm-up-to-main running order, teach-time and play-time estimates, and swaps for the non-gamers or the one player who hates losing.
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。
Simulate the acquirer's diligence team hunting for reasons to cut your price — their internal red-flags memo with a price-chip estimate per finding. Use when asked to red-team my company before a sale, how will an acquirer attack our valuation, pre-diligence audit, or what will DD find. Produces the acquirer's internal memo (revenue quality, key-person, tech debt, concentration, legal) and a debrief on which flags are fixable before a process.
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。