Finance Billing Ops

affaan-m/ECC/skills/finance-billing-ops

作者 affaan-mef648e01899ba3e8dc6371642deaaf64b4477775無授權條款275K 個星標收錄於 2026年10月9日更新於 2026年10月9日儲存庫4 天前更新

Evidence-first revenue, pricing, refunds, team-billing, and billing-model truth workflow for ECC. Use when the user wants a sales snapshot, pricing comparison, duplicate-charge diagnosis, or code-backed billing reality instead of generic payments advice.

僅含說明Business & Finance
AI 產生的概覽

以證據為先的收入、定價、退款、團隊計費與程式碼級計費事實工作流程。

功能
引導營運人員進行結構化的計費調查:整理即時或快照計費資料(銷售、訂閱、失敗結帳、退款、爭議、重複訂閱),分類客戶事件,並檢查權益、席次與配額行為的程式碼路徑。產出固定格式報告,包含快照、客戶影響、產品事實、決策與產品缺口等部分。同時列出可搭配使用的相關 ECC 技能。
適用情境
適用於需要銷售或 MRR 快照、定價或競品比較、重複扣款診斷,或想確認團隊計費與按席次計費是否真實存在的情況。適合同時涉及收入事實與實作事實的問題。
執行需求
僅為說明文件,不含指令碼。需要存取計費資料(即時或已儲存的快照),若要提出程式碼級結論還需存取相關產品程式碼庫;文中引用其他 ECC 原生技能,但未隨附這些技能。

Finance Billing Ops

Use this when the user wants to understand money, pricing, refunds, team-seat logic, or whether the product actually behaves the way the website and sales copy imply.

This is broader than customer-billing-ops. That skill is for customer remediation. This skill is for operator truth: revenue state, pricing decisions, team billing, and code-backed billing behavior.

Skill Stack

Pull these ECC-native skills into the workflow when relevant:

  • customer-billing-ops for customer-specific remediation and follow-up
  • research-ops when competitor pricing or current market evidence matters
  • market-research when the answer should end in a pricing recommendation
  • github-ops when the billing truth depends on code, backlog, or release state in sibling repos
  • verification-loop when the answer depends on proving checkout, seat handling, or entitlement behavior

When to Use

  • user asks for Stripe sales, refunds, MRR, or recent customer activity
  • user asks whether team billing, per-seat billing, or quota stacking is real in code
  • user wants competitor pricing comparisons or pricing-model benchmarks
  • the question mixes revenue facts with product implementation truth

Guardrails

  • distinguish live data from saved snapshots
  • separate:
    • revenue fact
    • customer impact
    • code-backed product truth
    • recommendation
  • do not say "per seat" unless the actual entitlement path enforces it
  • do not assume duplicate subscriptions imply duplicate value

Workflow

1. Start from the freshest billing evidence

Prefer live billing data. If the data is not live, state the snapshot timestamp explicitly.

Normalize the picture:

  • paid sales
  • active subscriptions
  • failed or incomplete checkouts
  • refunds
  • disputes
  • duplicate subscriptions

2. Separate customer incidents from product truth

If the question is customer-specific, classify first:

  • duplicate checkout
  • real team intent
  • broken self-serve controls
  • unmet product value
  • failed payment or incomplete setup

Then separate that from the broader product question:

  • does team billing really exist?
  • are seats actually counted?
  • does checkout quantity change entitlement?
  • does the site overstate current behavior?

3. Inspect code-backed billing behavior

If the answer depends on implementation truth, inspect the code path:

  • checkout
  • pricing page
  • entitlement calculation
  • seat or quota handling
  • installation vs user usage logic
  • billing portal or self-serve management support

4. End with a decision and product gap

Report:

  • sales snapshot
  • issue diagnosis
  • product truth
  • recommended operator action
  • product or backlog gap

Output Format

text
SNAPSHOT- timestamp- revenue / subscriptions / anomalies
CUSTOMER IMPACT- who is affected- what happened
PRODUCT TRUTH- what the code actually does- what the website or sales copy claims
DECISION- refund / preserve / convert / no-op
PRODUCT GAP- exact follow-up item to build or fix

Pitfalls

  • do not conflate failed attempts with net revenue
  • do not infer team billing from marketing language alone
  • do not compare competitor pricing from memory when current evidence is available
  • do not jump from diagnosis straight to refund without classifying the issue

Verification

  • the answer includes a live-data statement or snapshot timestamp
  • product-truth claims are code-backed
  • customer-impact and broader pricing/product conclusions are separated cleanly

來源與署名

來源:affaan-m/ECC位於skills/finance-billing-ops提交ef648e0

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