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burn-test-盈利能力测试

你的财务总监。在花钱之前建立企业的单位经济模型:每个单位在扣除直接成本后的盈利、计划销量下的实际利润率、每日盈亏平衡点、第一年逐月盈利、回本前所需现金、创业投入多久能收回,以及价格下降、销量低迷或成本上升时会发生什么。每个数字都可追溯到用户可核查的输入。当用户说“计算利润率”、“做一下数字”、“这个能盈利吗”、“盈亏平衡”、“单位经济”、“启动需要多少钱”或“让财务总监算算”时使用。

burn-test-盈利能力测试 是什么?

burn-test 是一个为 AI 助手(如 Claude Code、Cursor 或 Codex)设计的工具技能,旨在帮助创业者或产品经理在花钱之前快速建立清晰的单位经济模型。它通过一个简单的 JSON 输入文件(包含单位售价、可变成本、固定月费、启动成本、计划销量、每月爬坡销量和最大产能),自动计算单位贡献利润、固定成本、每日盈亏平衡点、计划销量下的利润率、第一年逐月财务预测、启动资金回收期以及多种“假设”场景(降价 10%、销量降低 20%、单位成本上升 15% 等)。该技能强调所有数字必须可追溯到用户提供的真实引用、发票、租赁合同或公开价格列表,优先使用实测数据,估算值需明确标注并说明理由。它支持多种系统(通过 Python 脚本运行),并在输出中提供一份“财务总监报告”,以通俗语言指出最可能失败的风险点、未验证需求下的悲观场景、对利润影响最大的关键变量、所需现金以及改善利润率的三种具体方法。最终输出三个文件:founder/numbers.json(输入)、founder/cfo.md(完整财务报告)、founder/cfo-sources.md(数据来源记录)。

兼容平台✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/peaknr35/shark-Tank-proof/tree/main/skills/burn-test

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文档

burn-test-盈利能力测试 是做什么的?

那个问“这要花多少钱?”的人。利润率决定一个好主意是否能成为一门生意。这个技能会找到它们,每个数字都可追溯到输入,并直白地告诉你这些输入中有多少是真实的。

首先阅读 ${CLAUDE_SKILL_DIR}/../receipts/rules.md。

此文件夹中的工具:

python3 "${CLAUDE_SKILL_DIR}/unit_economics.py" founder/numbers.json --out founder/cfo.md

步骤 1:收集输入

编写 founder/numbers.json(形状:此文件夹中的 example.json,以一家堂食抹茶店为例)。它需要:

字段输入内容
unit一次销售的单位:一杯、一单、一个客户月、一个座位
price未税单价
variable一个单位的成本:原料、包装、运费、刷卡手续费、销售佣金
fixed_monthly每月固定支出:租金、工资、软件、保险
startup开业前一次性支出:押金、装修、设备、首批库存、推广广告
plan_per_day运营稳定后的日销量
ramp_per_day12 个数字:第一年每个月的实际销量
capacity_per_day物理日最大产能(如有上限)

数字来源,按以下优先级:

  1. 用户自己的报价、发票、租赁合同和供应商价格清单。
  2. 用户可核实的公开价格(供应商价格清单、房东的挂牌信息、支付处理商的公开费率)。在 founder/cfo-sources.md 中,在数字旁边写下来源。
  3. 你的估算值,必须明确标注为估算,并附上推理过程。切勿将估算值当作事实呈现。

将每个输入记录在账本中,类别为 cost(成本)(价格输入类别为 price):报价、发票、租赁合同或公开价格页面为 MEASURED(已测量),并附上凭据 ID;估算值为 PLANNED(已计划)。计划报告会显示有多少成本是有凭据的。

询问用户只有他们才知道的信息(如租金报价、他们要支付的工资)。如果存在 founder/pricing.md 或 founder/pitch.md,则使用其中的价格。

爬坡销量是计划最容易出问题的地方。 第一个月几乎永远不会达到计划销量。如果进行过买家调研,则使用其购买率和首月购买量来验证爬坡销量的合理性(founder/panel/results.md),并说明你是如何做到的。调研数据是上限;如果还没有真实买家承诺购买,诚实的爬坡销量应低于调研建议值,绝不能更高。

步骤 2:运行工具

python3 "${CLAUDE_SKILL_DIR}/unit_economics.py" founder/numbers.json --out founder/cfo.md

它会输出:单位利润表和贡献毛利(每次销售扣除自身成本后的剩余)、固定成本、每日盈亏平衡点、计划销量下的利润率、第一年逐月数据、第一年营业利润和扣除启动成本后的结果、回本前所需现金、创业资金回收月份,以及一个假设分析表(价格 -10%、销量 -20%、单位成本 +15%)。它会标记:价格低于可变成本、盈亏平衡点超过产能、第一年亏损以及回收期超过 12 个月的情况。

无需编辑文件即可运行假设场景:

python3 "${CLAUDE_SKILL_DIR}/unit_economics.py" founder/numbers.json --price 7.00
python3 "${CLAUDE_SKILL_DIR}/unit_economics.py" founder/numbers.json --volume 0.8

步骤 3:财务总监报告

在 founder/cfo.md 顶部添加简短段落,用通俗语言说明:

  • 残酷真相:最可能导致失败的数字,以及有多少输入是报价而非估算(“11 项成本中 4 项有报价;爬坡销量是猜测”)。
  • 悲观场景:运行 --volume 0.5 并用一句话报告结果。如果没有真实的客户需求证据,这个场景的可能性与计划场景相同。
  • 利润率:计划销量下的利润率,以及单位贡献毛利。
  • 关键指标:对结果影响最大的单个成本或假设(通常是爬坡销量、租金或价格),附上证明这一点的假设分析结果。
  • 现金:创始人回本前需要多少资金。
  • 提高利润率的三种方法,每种方法说明它改变哪个数字以及改变多少(直接运行假设分析,不要猜测)。
  • 关于资金的董事会条件(founder/board.md)是否满足。

规则

  • 报告中的每个数字必须来自工具的输出或你可命名的输入。
  • 模型的每个输出(利润率、盈亏平衡点、第一年数据、回收期)都是 PLANNED(计划值)。切勿将预测的利润率称为“实际利润率”或“真实结果”。
  • 收入为未税收入;说明用户所在市场是否需在此基础上附加销售税。
  • 这不是财务、税务或法律建议。在资金流动前,务必建议会计核查公司结构、工资成本和税务,并明确声明一次。

输出

founder/numbers.json、founder/cfo.md、founder/cfo-sources.md。下一步:/kill-or-build 使用这些数字做出判断;如果利润率微薄,则使用 /litmus。

Individual skills in this repo

This repo contains 5 individual skills — each has its own dedicated page.

dealbreaker

Builds an offer too good to refuse. Lists every problem the buyer hits on the way to the result they want, turns each into a solution, trims to what is cheap to deliver and valuable to the buyer, and stacks it with honest bonuses, a guarantee the CFO can afford, real urgency and a clear name. Scores it on the value equation (outcome, likelihood, time, effort) and re-tests it on a quick buyer panel. Use when the user says "make my offer better", "why won't people buy", "what should I include", "guarantee", "bonuses", "grand slam offer", or after the panel shows people passing.

handshake

Turns the founder folder into the thing that gets one real person to say yes to the next step: a one-page pilot offer for a customer, an NSF Project Pitch or grant answer for a funder, an investor or lender one-pager, a business case for a boss, or an invite for the people who will use it. Always writes the one-sentence, three-sentence and three-minute versions first. Builds only from claims in the evidence ledger that the audience may see, never from simulated buyers, and checks the finished pitch with the ledger before it goes out. Use when the user says "pitch this", "write a pilot offer", "one-pager", "grant pitch", "NSF pitch", "deck for", "email this customer", "business case", or "what do I send them".

kill-or-build

Your business planner. Compiles everything the other Shark Tank Proof skills wrote (the board's verdict, the competitors, the buyer panel, pricing, the offer, the CFO's numbers, marketing, brand, operations, the launch plan and the evidence ledger) into one business plan with a verdict at the top that is computed, never written by hand: Profitable (the numbers pass and a real buyer has paid, signed or booked), Unproven (works on paper, no real buyer yet), Not yet (with the failing numbers) or Incomplete. A simulated panel can fail a plan but never pass one. Adds an executive summary and a one-page version. Use when the user says "write my business plan", "put it all together", "is it profitable", "give me the plan", or at the end of the Shark Tank Proof pack.

shark-board

Your board of directors, built to disagree with you. Puts a business idea in front of a four-member board, each a sub-agent reading the idea through one published framework: the Offers lens (from Alex Hormozi's $100M Offers), the Monopoly lens (from Peter Thiel's Zero to One), the Product lens (from Walter Isaacson's biography of Steve Jobs) and the Evidence lens (from Rob Fitzpatrick's The Mom Test), which scores only what real people have done. Each member scores the idea, names what would kill it and the cheapest test that would prove it, and votes fund, fund with conditions, or pass. Use when the user says "test my business idea", "would this work", "pressure-test this", "what would a board say", "is this a good business", or starts the Shark Tank Proof pack on a new idea.

truth-serum

The consumer panel. Spins up a swarm of buyer sub-agents (default 100, --quick for 20) trained on the user's target customer, each with a different income, age, buying behaviour and objection, shows every one the same pitch, and runs the business through 100 buyer scenarios to see who buys, who doesn't, and why. Tallies the answers into buy rates by segment, the reasons people pass in their own words, what would flip a no, and price answers for litmus. Every result is labelled SIMULATED: it finds objections and the questions to ask real buyers, and never counts as demand. Use when the user says "would people buy this", "test it on customers", "run the consumer panel", "simulate buyers", "who is my customer", or "validate demand".

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