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财务计费运营

基于证据的收入、定价、退款、团队计费和计费模型真实工作流程,用于ECC。当用户想要销售快照、定价比较、重复收费诊断或基于代码的计费现实而非通用支付建议时使用。

财务计费运营 是什么?

此技能专为ECC平台的运营人员设计,旨在提供基于代码和实时数据的计费真相,而非泛泛的支付建议。它能够帮助用户快速获取销售快照、进行定价比较、诊断重复收费问题,并验证产品计费行为是否与网站宣传一致。技能支持与`customer-billing-ops`、`research-ops`、`github-ops`等ECC原生技能协同工作,以处理从客户特定补救到市场研究等多种场景。其工作流程强调从最新计费证据入手,分离客户事件与产品真相,并检查代码层面的计费实现路径,最终输出包含销售快照、客户影响、产品真相、决策和产品差距的结构化报告。该技能有助于避免常见陷阱,如混淆失败尝试与净收入、仅凭营销语言推断团队计费等。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/finance-billing-ops

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

财务计费运营 是做什么的?

当用户想要了解资金、定价、退款、团队席位逻辑,或者验证产品的实际行为是否与网站和销售文案所述一致时使用此技能。

此技能比customer-billing-ops更广泛。customer-billing-ops用于客户补救。此技能用于运营真相:收入状态、定价决策、团队计费和基于代码的计费行为。

技能栈

在相关时,将以下ECC原生技能拉入工作流程:

  • customer-billing-ops:用于特定客户的补救和跟进
  • research-ops:当竞争对手定价或当前市场证据重要时
  • market-research:当答案应以定价建议结束时
  • github-ops:当计费真相取决于兄弟仓库中的代码、积压或发布状态时
  • verification-loop:当答案取决于验证结账、席位处理或权限行为时

何时使用

  • 用户询问Stripe销售、退款、MRR或近期客户活动
  • 用户询问团队计费、按席位计费或配额堆叠在代码中是否真实存在
  • 用户想要竞争对手定价比较或定价模型基准测试
  • 问题混合了收入事实与产品实现真相

护栏

  • 区分实时数据与保存的快照
  • 区分:
    • 收入事实
    • 客户影响
    • 代码支持的产品真相
    • 建议
  • 除非实际的权限路径强制执行,否则不要说“按席位”
  • 不要假设重复订阅意味着重复价值

工作流程

1. 从最新的计费证据开始

优先使用实时计费数据。如果数据不是实时的,明确声明快照时间戳。

规范化以下信息:

  • 已支付销售
  • 活跃订阅
  • 失败或不完整的结账
  • 退款
  • 争议
  • 重复订阅

2. 将客户事件与产品真相分离

如果问题是客户特定的,首先分类:

  • 重复结账
  • 真实团队意图
  • 自助服务控制故障
  • 未满足的产品价值
  • 支付失败或设置不完整

然后将其与更广泛的产品问题分离:

  • 团队计费是否真实存在?
  • 席位是否实际被计数?
  • 结账数量是否改变权限?
  • 网站是否夸大当前行为?

3. 检查代码支持的计费行为

如果答案取决于实现真相,检查代码路径:

  • 结账
  • 定价页面
  • 权限计算
  • 席位或配额处理
  • 安装与用户使用逻辑
  • 计费门户或自助服务管理支持

4. 以决策和产品差距结束

报告:

  • 销售快照
  • 问题诊断
  • 产品真相
  • 建议的运营操作
  • 产品或积压差距

输出格式

快照
- 时间戳
- 收入 / 订阅 / 异常

客户影响
- 谁受到影响
- 发生了什么

产品真相
- 代码实际做了什么
- 网站或销售文案声称了什么

决策
- 退款 / 保留 / 转化 / 无操作

产品差距
- 需要构建或修复的确切后续项目

陷阱

  • 不要将失败尝试与净收入混为一谈
  • 不要仅从营销语言推断团队计费
  • 当有当前证据可用时,不要凭记忆比较竞争对手定价
  • 不要在未分类问题的情况下从诊断直接跳到退款

验证

  • 答案包含实时数据声明或快照时间戳
  • 产品真相声明基于代码
  • 客户影响与更广泛的定价/产品结论被清晰分离

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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