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

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

santa-method

通过双评审智能体对结果进行对抗式校验，提升输出发布前的可靠性

customer-billing-ops

帮助团队处理订阅、退款、流失判断与收入相关的客户计费操作。