spread1000-cost-estimator

name	spread1000-cost-estimator
description	Estimate Azure costs based on architecture design. Generate monthly and full research period (~180 days) cost estimates and produce cost breakdowns required for SPReAD budget applications. Use when estimating Azure costs, planning budgets, or filling in expense sections of the proposal.

Cost Estimator

Calculate costs from the Azure architecture design and generate estimates aligned with SPReAD budget application requirements.

Use This Skill When

• Azure architecture design is complete and costs need to be estimated
• Creating an expense plan for the SPReAD proposal
• Evaluating cost optimization options (Spot VMs, Reserved Instances, etc.)

Required Inputs

• output/{project-name}/phase1-azure-architecture.md (Azure architecture design)
• Research period (~180 days ≈ ~6 months)
• Estimated monthly usage hours (GPU uptime, etc.)

Workflow

1. Parse the architecture design: Extract resource list, SKUs, and quantities

2. Retrieve unit prices (MANDATORY — using LLM memory/estimated values is PROHIBITED): The agent must retrieve actual latest prices using the steps below and attach the results to the estimate document. If web fetch or API calls fail, the estimate document must state "Price not retrieved" and display a bold warning indicating the value is estimated.

   Step 2a: Call the Azure Retail Prices API (recommended, highest priority)

   Retrieve JSON via browser, fetch_webpage, or curl using the following URL pattern:

   https://prices.azure.com/api/retail/prices?$filter=serviceName eq 'Virtual Machines' and armRegionName eq 'japaneast' and armSkuName eq 'Standard_ND96asr_v4'
   

   • Replace armSkuName with the target VM (e.g., Standard_NC24ads_A100_v4, Standard_HB120rs_v3)
   • Set armRegionName to the user-specified region (default: japaneast)
   • Use retailPrice (USD/hour) from the response JSON as the unit price
   • Distinguish Consumption (Pay-as-you-go) and Reservation (RI) via the type field
   • For Spot pricing: add and priceType eq 'Consumption' and skuName eq '... Spot' to $filter

   Step 2b: Web-fetch Azure official pricing pages (fallback if API fails)

   • Azure VM Pricing — GPU VM Pay-as-you-go / Spot / RI pricing
   • Azure Storage Pricing — Blob / ADLS Gen2
   • Azure ML Pricing — ML Compute
   • Azure AI Services Pricing — OpenAI / AI Foundry
   • Azure Managed Lustre Pricing — HPC storage
   • Azure Cosmos DB Pricing — Graph DB
   • Azure AI Search Pricing — Search service

   Step 2c: Price items to retrieve

   • Pay-as-you-go price (USD/hour)
   • Reserved Instance 1-year and 3-year prices
   • Spot VM prices
   • Applicability of Azure for Research / Academic discounts

   Step 2d: Record-keeping

   • Price retrieval date must be recorded in the estimate document
   • Price source (API URL or page URL) must be recorded in the estimate document
   • Exchange rate: use the TTM rate as of the retrieval date, and cite the source

3. Cost calculation:

   • Monthly cost / 月額コスト (normal usage and peak usage)
   • Total cost / 総額コスト for the full research period / 研究期間 (~180 days)
   • Comparison of cost optimization options
   • Verify that 直接経費 fits within the 予算上限（500万円以下）
   • 算定根拠の記載: 各リソースの「算定根拠」列に以下を記入する
     • 単価の出典（API URL または公式ページ URL）
     • 使用量の算定方法（例: 平日8h × 20日 = 月160時間）
     • 計算式（例: $3.50/h × 160h = $560/月）

4. Generate budget plan: Save as output/{project-name}/phase2-cost-estimate.md

   • Reuse assets/cost-estimate-template.md when producing the estimate

5. Validation: Confirm alignment with the SPReAD budget ceiling (直接経費 ≤ ¥5M)

Deliverables

• output/{project-name}/phase2-cost-estimate.md: Cost estimate document (complete version)

Quality Gates

• Unit price sources are documented for all resources
• Estimates are presented at two levels: monthly and total
• Cost optimization options (Spot VMs, RI, shutdown schedules) have been evaluated
• Alignment with SPReAD budget requirements (直接経費 ≤ ¥5M, 間接経費 30%) is confirmed
• Exchange rate (JPY/USD) is stated
• 全リソースの「算定根拠」列に単価出典・使用量根拠・計算式が記載されている
• 「6. 算定根拠の詳細」セクションに価格取得ソース・為替レート根拠・使用量算定根拠が記載されている

HARD GATE — Price Verification

Before finalizing the estimate, the following checks must be executed. If any check FAILs, mark the estimate as "Draft (prices unverified)" and warn the user.

• Unit prices for all VM SKUs have been retrieved from the Azure Retail Prices API or official pricing pages
• Retrieval date is recorded in the estimate document
• Source URLs are recorded in the estimate document
• Exchange rate source is cited
• No line item has been calculated solely from LLM memory/estimated values

Gotchas

• 🚫 Do NOT use historical prices from LLM training data. The agent must call the Azure Retail Prices API (prices.azure.com) via fetch_webpage or terminal curl, and extract retailPrice from the response JSON. If the API call is skipped and estimated values are used, display a bold warning ⚠️ 価格未検証（推定値） in the estimate document
• The Azure Retail Prices API (prices.azure.com) returns the latest unit prices in JSON. Default armRegionName to japaneast and adjust to the user's preferred region
• Spot VMs offer up to 90% discount but carry preemption risk. Assume training interruption tolerance (checkpointing) is in place
• Azure for Research program discount rates vary by application. List them as reference values, not confirmed amounts
• Do not overlook hidden costs / 隠れコスト (データ転送, log storage, Key Vault operations)

Validation Loop

1. Generate the cost estimate
2. Check:
   • Are all resources covered?
   • Is the total within the budget ceiling?
   • Have cost optimization opportunities been explored?
3. If any check fails:
   • Consider VM size downgrade or switching to Spot VMs
   • Propose usage optimization (e.g., overnight shutdown schedules)
   • Recalculate
4. Finalize the deliverable only after all gates pass