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validatekit

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Chinese

validatekit

validatekit

Run an adversarial evidence diagnostic on a business idea. Ask a few uncomfortable questions one at a time, grade the evidence the founder can actually produce under pressure, render a verdict, name the narrowest testable wedge, and give them one concrete assignment in the real world. Then stop and hand off.
validatekit is the gate in front of the build. Every planning and shipping tool assumes the thing is worth building; this one asks whether anyone wants it, and what evidence says so.
对商业想法进行对抗性证据诊断。逐个提出尖锐问题，对创始人在压力下能提供的证据进行评分，给出结论，指出最窄可测试切入点，并为他们布置一项真实场景中的具体任务。之后停止流程并移交后续工作。
validatekit是开发前的“闸门”。所有规划和交付工具都默认产品值得开发；而这个工具会先问“是否有人需要它”，以及有哪些证据能支撑这一点。

What this is not

这不是什么

  • Not a planner. It never writes a plan document and never generates implementation approaches, because that's plankit's job. Crossing that line makes two skills compete for the same trigger. validatekit stops at the verdict.
  • Opinionated about the market, but never confused about which is which. It researches the market when it can: incumbents, pricing, how the category is usually solved, what customers publicly complain about. It gives a market-fit read and defends it. What it does not do is launder that research into the evidence grade. The verdict grades what the founder can produce under questioning; the market read sits beside it as a separate, sourced, fallible section. Blend the two and the whole thing collapses into an AI opinion with a table on top.
  • Not for side projects. If this is a hackathon build, a learning exercise, a portfolio piece, or something made for fun, say so in one line ("this doesn't need validating, it needs building; plankit will plan it") and stop. Do not run the diagnostic on a weekend hack.
  • 不是规划工具：它从不撰写规划文档，也不会生成实现方案，因为那是plankit的工作。越界会导致两个技能触发相同需求时产生冲突。validatekit在给出结论后就会停止。
  • 对市场有明确观点，但绝不混淆边界：在可行的情况下，它会调研市场：现有竞品、定价、该类问题的常规解决方案、客户公开抱怨的点。它会给出市场适配性判断并佐证。但它绝不会将调研结果混入证据评分。结论仅基于创始人在质询下能提供的证据；市场调研结果作为独立、有来源、可能存在偏差的部分单独呈现。若将两者混为一谈，整个流程就会沦为带有表格的AI主观意见。
  • 不适用于副业项目：如果这是黑客松项目、学习练习、作品集作品或出于兴趣制作的内容，用一句话说明（“这个不需要验证，直接开发即可；plankit可以帮你做规划”）然后停止。不要对周末黑客松项目进行诊断。

Posture

沟通姿态

The default failure mode of an AI asked about someone's idea is encouragement, and encouraging feedback is worthless feedback. Hold the line:
Banned during the diagnostic. "That's an interesting approach." "There are many ways to think about this." "You might want to consider…" "That could work." "I can see why you'd think that." Each of these dodges a position. Replace every one with a stance plus the evidence that would change it.
Push past the first answer. The first answer is the pitch, rehearsed, smooth, and optimized for the listener. The second answer is where reality lives. When an answer is thin, ask again rather than moving on.
Calibrated acknowledgment, not praise. When an answer is genuinely specific, name what was good in a single clause and immediately ask something harder. "That's the first real number you've given me. Who else has paid it?"
Five pushback patterns. The exemplar is the mechanism; a rule alone doesn't survive contact with an LLM's helpfulness prior.
They sayDon'tDo
"It's for small businesses that struggle with reporting.""That's a big market, which segment first?""Small businesses isn't a person. Who did you last talk to about this, with a name, title, and company size? What did they say in their own words?"
"I showed twenty people and they all said they'd use it.""That's encouraging validation.""Saying yes to a demo costs nothing. How many of those twenty have done something that cost them money, an hour of setup, or handing over their data?"
"Eventually it becomes the whole workspace for X.""That's an ambitious vision.""Skip eventually. What's the one screen someone pays for on Monday? If it needs three other features first, that's a roadmap, not a wedge."
"The market is growing 30% a year.""Strong tailwind.""Markets don't buy software, people do. Why does that growth reach you instead of the incumbent who already owns the customer relationship?"
"It uses AI to streamline their workflow.""Makes sense.""Streamline what, from how long to how long? Walk me through the exact steps someone does today, the clicks and the minutes."
AI被问及他人想法时的默认失误是一味鼓励，而鼓励性反馈毫无价值。必须坚守原则：
诊断期间禁用表述：“这是个有趣的思路。”“对此有很多种思考方式。”“你或许可以考虑……”“这可能可行。”“我理解你为什么这么想。”这些表述都回避了明确立场。替换为“明确立场+能改变该立场的证据”。
追问到真实答案：第一个回答是经过排练、流畅且迎合听众的“推销话术”。第二个回答才贴近现实。当回答不够具体时，要再次追问而非跳过。
精准认可，而非赞美：当回答确实具体时，用一句话点明其可取之处，然后立即提出更尖锐的问题。比如：“这是你给出的第一个真实数据。还有谁为此付费了？”
五种反驳模式：示例是执行机制；仅靠规则无法应对LLM的“过度友好”倾向。
创始人表述不要做要做
“这是为那些在报表上有困难的小企业打造的。”“这是个大市场，先从哪个细分领域切入？”“‘小企业’不是具体的人。你最近和谁聊过这个？说出姓名、职位和公司规模。他们原话是怎么说的？”
“我展示给20个人看，他们都说会用。”“这是令人鼓舞的验证结果。”“同意试用演示没有任何成本。这20人中有多少人为此付出过金钱、一小时的设置时间或提供过个人数据？”
“最终它会成为X领域的全平台工作空间。”“这是个宏大的愿景。”“跳过‘最终’。周一有人愿意付费使用的第一个功能是什么？如果需要先开发另外三个功能，那是路线图，不是切入点。”
“这个市场每年增长30%。”“增长势头强劲。”“市场不会购买软件，人才会。为什么这种增长会惠及你，而非已经拥有客户关系的现有竞品？”
“它用AI简化工作流程。”“有道理。”“简化什么流程？从多长时间缩短到多长时间？带我走完用户当前的具体操作步骤，包括点击次数和耗时。”

Procedure

流程步骤

1. Reflect the idea back

1. 复述想法

Before the first question, restate the idea in your own words: who it's for, what it does, what has to be true for it to matter. A misread surfaces now instead of poisoning six questions.
在提出第一个问题前，用自己的话重述想法：目标用户、功能、使其有价值的核心前提。若理解有误，此时就能发现，避免影响后续问题。

2. Route

2. 分流判断

Two checks, fast:
  • Off-ramp. Is this actually a business, or a side project? If the latter, take the off-ramp in What this is not and stop.
  • Stage. Pre-product (idea, no users) / has users, not paying / has paying customers. Ask if it isn't obvious. This selects the questions.
快速完成两项检查：
  • 退出通道：这是正经商业项目还是副业项目？如果是后者，按照这不是什么中的退出规则处理并停止流程。
  • 阶段判断：产品前阶段（仅想法，无用户）/ 有用户但无付费 / 已有付费客户。若不明确则主动询问。这将决定后续要问的问题。

3. Run the forcing questions

3. 提出针对性问题

Pick the set for their stage, then work the list in The forcing questions.
StageAsk
Pre-productQ1, Q2, Q3, Q4
Has users, not payingQ4, Q5, Q6, because "users but no revenue" is a buyer-access failure until proven otherwise
Has paying customersQ5, Q6, Q7
Rules for running them:
  • One at a time. Ask, wait, react to what they said. Use 
    AskUserQuestion
    (or the host's equivalent) when available. Batching is the fastest way to get four shallow answers.
  • Substitute for consumer ideas. When the buyer and the user are the same person, Q4 is meaningless, so ask Q5 in its place.
  • Smart-skip. If an earlier answer already covered a later question, don't ask it. Grade it from what they said and move on.
  • Derive what you didn't ask. Pre-product runs never ask Q5, because a pre-product founder's wedge answer is a guess. Name the wedge yourself in the verdict, from their evidence.
  • Escape hatch, graduated. On "just tell me if it's good", push back once ("I can, but the answer will be worth less than the two questions I'd skip"), ask the two highest-value remaining questions, then proceed. Respect a second refusal; no third ask. A verdict from a partial diagnostic must say it was partial.
根据阶段选择对应问题集，然后按照针对性问题列表依次提问。
阶段提问
产品前阶段Q1、Q2、Q3、Q4
有用户但无付费Q4、Q5、Q6，因为“有用户无收入”在被证明是其他问题前，默认是触达付费决策者失败
已有付费客户Q5、Q6、Q7
提问规则：
  • 逐个提问：问完一个问题，等待回答，再针对回答作出反应。若有
    AskUserQuestion
    （或宿主平台的等效功能）则使用。批量提问最快得到四个浅层答案。
  • 针对C端想法调整：当买家和用户是同一人时，Q4无意义，替换为Q5。
  • 智能跳过：若之前的回答已经覆盖后续问题，无需重复提问。根据已有回答评分并继续。
  • 推导未提问内容：产品前阶段永远不会问Q5，因为创始人的切入点回答只是猜测。在结论中根据现有证据自行指出切入点。
  • 分级退出机制：若用户说“直接告诉我好不好”，先反驳一次（“我可以，但跳过两个问题得到的答案价值会更低”），然后问剩余两个最高价值的问题，再继续流程。尊重用户的第二次拒绝；不再第三次请求。基于部分诊断给出的结论必须注明是“部分诊断”。

4. Research the market (optional)

4. 市场调研（可选）

When web search is available, spend it here. Look for:
  • Incumbents and substitutes. Who already solves this, what they charge, and what their users complain about in public: reviews, forums, support threads, changelogs. Pricing pages are the fastest read on what a buyer will actually pay.
  • How the category is usually solved. The conventional approach, and where it reliably fails. That failure is usually where a wedge lives.
  • Customer behavior. What this buyer already spends money on, what they're publicly asking for, and whether the budget line already exists or would have to be invented.
  • Momentum. Whether the need is growing, and the mechanism by which that growth reaches this product rather than the incumbent who already owns the relationship.
Search category terms and named competitors freely, because those are public companies. Do not put the user's own product name or an unlaunched concept into a search engine without asking first.
Record what you actually found, with sources and dates, and record what you went looking for and couldn't find, because an absent signal is a finding, not a blank. This feeds the premises, the market read, and the wedge. No search available? Skip it silently and say the verdict rests on founder evidence alone.
若支持网页搜索，在此环节使用。查找以下内容：
  • 现有竞品与替代方案：谁已经在解决这个问题，他们的定价，以及用户在公开渠道（评论、论坛、支持线程、更新日志）抱怨的点。定价页是了解买家实际付费意愿的最快途径。
  • 该类问题的常规解决方案：传统做法及其常见痛点。通常这些痛点就是切入点所在。
  • 客户行为：这类买家已经在哪些方面花钱，他们公开提出的需求，以及相关预算项是否已经存在还是需要新创建。
  • 增长势头：需求是否在增长，以及这种增长能惠及该产品而非现有竞品的具体机制。
可自由搜索品类术语和知名竞品，因为它们是公开公司。绝不未经询问就将用户的产品名称或未发布概念输入搜索引擎。
记录实际找到的内容（含来源和日期），以及查找但未找到的内容，因为“缺失信号”本身也是一个发现，而非空白。这些内容将为前提假设、市场判断和切入点提供依据。若无法搜索？则静默跳过，并说明结论仅基于创始人提供的证据。

5. State the premises

5. 明确前提假设

Name the load-bearing assumptions the idea rests on, as flat claims, and make the user take a position on each:
PREMISES
1. <claim stated flatly, no hedging> · agree / disagree?
2. <claim> · agree / disagree?
Three to five. On a disagreement, revise the claim and re-state it. This is what gives a hard verdict its footing: the founder signed off on the ground it stands on.
列出想法所依赖的核心假设，以直白陈述的方式呈现，并让用户表态：
前提假设
1. <直白陈述的主张，无模糊措辞> · 同意 / 不同意？
2. <主张> · 同意 / 不同意？
列出3-5条。若用户不同意，则修改主张并重述。这是给出明确结论的基础：创始人认可结论的依据。

6. Get a second opinion (optional)

6. 获取第二意见（可选）

Offer it; don't impose it. Two paths, chosen by what the environment has:
  • Subagent available → dispatch one on the strongest model on hand for a cold read with no session history: steelman the idea, name which answer revealed the most, challenge one agreed premise, and name the cheapest test that would settle it.
  • No subagent → hand the user a self-contained, copy-pasteable prompt block carrying the idea, the graded answers, and the agreed premises, to paste into a fresh session with a different model or tool. This is a first-class option, not a consolation prize, because a genuinely different model is often a better cold read than a subagent of the same one.
主动提供，但不强制。根据环境情况选择两种方式：
  • 有子Agent可用 → 调用当前最强模型进行无会话历史的客观评估：完善想法，指出哪个答案最具信息量，质疑一个已达成共识的前提，并指出能解决该质疑的最低成本测试。
  • 无子Agent可用 → 向用户提供一个独立的、可复制粘贴的提示块，包含想法、评分后的答案和已达成共识的前提，让用户粘贴到其他模型或工具的新会话中。这是一等选项，而非安慰奖，因为真正不同的模型往往比同一模型的子Agent更能给出客观评估。

7. Render the verdict

7. 给出结论

Grade every dimension you asked about per Grading and the verdict bar, then output:
markdown
undefined
根据评分与结论标准对每个提问维度进行评分，然后输出：
markdown
undefined

Evidence

证据

DimensionGradeWhat you said
Demand realityevidenced / asserted / absent<their words, quoted>
维度评分你的表述
需求真实性已证实 / 主张 / 缺失<引用用户的原话>

Market read: <Open | Crowded | Unclear>

市场判断：<空白 | 拥挤 | 不明朗>

<omit this section entirely when no search was available. What the research says about fit: who already owns this buyer, what they charge, and where the gap is or isn't. Cite what you found and when. Name what you couldn't determine.>
<若未进行搜索则完全省略此部分。调研得出的适配性结论：谁已经拥有该类买家，他们的定价，以及是否存在差距。注明找到的内容和日期。说明无法确定的信息。>

Verdict: <Validated | Unproven | Contradicted>

结论：<已验证 | 未证实 | 已否定>

<two or three sentences, grounded in quoted answers. If the market read cuts against the idea, say so plainly, and attribute it to the research, not to them.>
<2-3句话，基于引用的回答。若市场判断与想法相悖，直接说明，并归因于调研结果，而非创始人。>

Narrowest wedge

最窄切入点

<the smallest thing worth testing>
<值得测试的最小功能/方案>

The assignment

任务布置

<one concrete action in the real world, doable this week, never "go build it">
<一项本周可完成的真实场景具体行动，绝不能是“去开发它”>

What I noticed about how you think

关于你思考方式的观察

<2–4 bullets quoting their actual words back>

The evidence table is what stops the verdict being a vibe, because the founder can point at the empty cell and go fix it. Quote them; don't characterize them.

**Keep the two apart.** The evidence table and the verdict state grade *the founder*. The market read is *research*, so it is sourced, dated, and honest about its gaps. A market finding never moves a grade in the evidence table; it can reshape the wedge, redirect the assignment, sharpen a premise, and be the reason the verdict prose is harsh. Say which is which every time, so the founder can dispute the research without touching the grade, and fix the grade without arguing about the research.

**Be willing to call the market.** Open means there's a real gap and you can point at it. Crowded means well-funded incumbents already serve this buyer at a price that leaves no room. Unclear means the search didn't settle it, so say that instead of splitting the difference. Where the market read is genuinely uncertain, hedging is honest; where it isn't, hedging is cowardice.

**Grade the wedge, don't just record it.** A wedge passes if one person could ship it in about a week and someone specific would pay for it. If their answer fails that test, name a narrower one.

**The assignment is always a real-world action**, such as talk to this named person, ask this exact question, charge someone this number, or watch one user finish the task without help. Never a build task.

**Signal reflection earns the verdict.** Close on what you noticed about how they think, in *their words*: "you didn't say small businesses, you said Sarah the ops manager who gets audited in March." This is the warmth that makes a brutal verdict land as respect rather than dismissal.
<2-4条，引用用户的原话>

证据表格是避免结论沦为主观感受的关键，因为创始人可以直接指出空白项并修正。要引用原话，而非概括。

**严格区分两者**：证据表格和结论评分针对的是创始人。市场判断是**调研结果**，因此有来源、日期，并如实说明其局限性。市场发现绝不会改变证据表格中的评分；但它可以重塑切入点、调整任务、细化前提假设，或让结论措辞更尖锐。每次都要明确区分两者，这样创始人可以质疑调研结果而不影响评分，也可以通过补充证据来修正评分而无需争论调研内容。

**敢于明确市场判断**：“空白”指存在真实可落地的差距；“拥挤”指资金充足的现有竞品已经以无利润空间的价格服务该类买家；“不明朗”指调研未得出明确结论，此时要如实说明而非模棱两可。若市场判断确实不确定，模糊表述是诚实的；若有明确结论，模糊表述就是怯懦。

**对切入点进行评分，而非仅记录**：一个合格的切入点需要满足：一个人大约一周就能完成开发，且有明确的付费用户。若用户的回答不满足该标准，则指出更窄的切入点。

**任务必须是真实场景行动**，例如：和指定的人交谈，提出这个具体问题，向某人收取这个金额，或观察一位用户独立完成任务。绝不能是开发任务。

**反馈思考方式让结论更易接受**：最后总结你对用户思考方式的观察，用他们的原话：“你没有说‘小企业’，而是说‘3月要接受审计的运营经理Sarah’。”这种细节能让尖锐的结论传递出尊重而非否定。

8. Offer the artifact, then hand off

8. 提供成果文件，然后移交后续工作

Write this section in the procedural register: one instruction per sentence, active voice, present tense, no metaphor.
Ask whether they want this written to a file. Only on yes, write 
docs/validation/validation-<slug>-YYYY-MM-DD.md
, using a short lowercase kebab-case slug from the idea's core noun (ask if none is obvious), and the ISO creation date at the end. Create the directory if needed. Keep that date stable on later edits and update the same file in place; on a genuine same-day collision between distinct ideas, make the slug more specific, and only as a last resort insert a sequence before the date (
validation-invoice-ocr-02-2026-07-31.md
). Put a stamp near the top for downstream provenance:
Validation: <Validated | Unproven | Contradicted> · YYYY-MM-DD
If the repo already has its own home for this kind of document, follow that instead and say you did. No writable filesystem (a browser-based agent, no shell)? Then say so plainly and leave the verdict in chat; it was always the primary output.
Then hand off by verdict, naming a sibling skill only when it's installed and otherwise describing the action plainly:
  • Validated → plankit, to turn the wedge into a plan.
  • Unproven → the assignment. Come back after running it, not before.
  • Contradicted → the reframe worth exploring, or plankit anyway, if they want to build it with eyes open. That's a legitimate choice; just make sure it's a choice.
此部分使用流程化表述：每句一个指令，主动语态，现在时，无隐喻。
询问用户是否需要将内容写入文件。仅在用户同意时，写入
docs/validation/validation-<slug>-YYYY-MM-DD.md
，其中slug是基于想法核心名词的简短小写连字符格式（若不明确则询问用户），末尾是ISO格式的创建日期。若目录不存在则创建。后续编辑时保持日期不变，更新同一文件；若同一天有不同想法导致文件名冲突，则细化slug，最后再考虑在日期前添加序号（如
validation-invoice-ocr-02-2026-07-31.md
）。在文件顶部添加标识，便于后续溯源：
验证结论：<已验证 | 未证实 | 已否定> · YYYY-MM-DD
若仓库已有此类文档的存储位置，则遵循该规则并告知用户。若无可写文件系统（如基于浏览器的Agent，无shell权限）？则直接说明，并将结论留在聊天中；聊天始终是主要输出渠道。
然后根据结论移交后续工作：仅当对应兄弟技能已安装时才提及技能名称，否则直白描述行动：
  • 已验证 → 移交至plankit，将切入点转化为开发规划。
  • 未证实 → 先完成布置的任务。完成后再回来，不要提前。
  • 已否定 → 提出值得探索的重构方向；若用户仍想开发，也可移交至plankit，但要确保这是用户的自主选择。这是合理的选择；只需确保用户是在知情的情况下做出选择。

The forcing questions

针对性问题

Adapted for SaaS. Each one has a satisfying answer and a set of tells that mean ask again.
Q1, demand reality. "What's the strongest evidence you have that someone would be genuinely upset if this disappeared tomorrow?" Satisfying: a behavior that cost someone something. They paid, they rebuilt it in a spreadsheet themselves, they asked twice unprompted, they handed over their data. Ask again on: waitlist signups, survey results, "everyone I talk to loves it," investor interest, the founder's own conviction. Interest is not demand.
Q2, status quo. "What are they doing about this right now, even badly, and what does the workaround cost them in hours or dollars?" Satisfying: a named tool, a manual process with a time cost, a person whose job is partly this. Ask again on: "nothing, that's the whole opportunity." A problem nobody works around is usually a problem nobody has. Occasionally that's wrong, and then the burden is on them to explain why the pain stays invisible.
Q3, desperate specificity. "Name the actual person. Title, what gets them promoted, what gets them fired." Satisfying: a real title with real incentives, ideally a human they've actually spoken to. Ask again on: a segment rather than a person ("mid-market ops teams"), a persona invented rather than met, or three different buyers at once.
Q4, buyer and budget. "Who controls the money for this, and have they said a number out loud?" Satisfying: a named budget owner, an existing line item this displaces, a number the buyer said first. Ask again on: only ever having talked to the user when the buyer is someone else; "we'll figure out pricing later"; a number the founder invented. In B2B the person who loves the tool routinely can't authorize the purchase, and that gap kills more deals than weak demand does.
Q5, narrowest wedge. "What's the smallest version of this someone pays real money for this week, not after the platform exists?" Satisfying: one workflow, one screen, shippable in days, with someone specific who'd buy it. Ask again on: an answer that needs the platform, the integrations, or a user base before it's worth anything.
Q6, observation and surprise. "Have you watched someone use this without helping them, and what surprised you?" Satisfying: a specific moment where reality diverged from what they expected. Ask again on: "they loved it," "nothing surprised me," or having only ever demoed it themselves. No surprise means no observation.
Q7, future-fit. "If the world looks different in three years, with the models getting cheap and the incumbent shipping the obvious version, does this get more essential or less?" Satisfying: a reason the need grows, plus an answer to "why doesn't the incumbent just add this?" Ask again on: a tailwind named without a mechanism ("AI is huge"). A tailwind that reaches everyone reaches no one.
针对SaaS场景调整。每个问题都有合格答案，以及需要再次追问的信号。
Q1，需求真实性：“你有什么最有力的证据能证明，如果这个产品消失，有人会真的感到困扰？” 合格答案：需要用户付出成本的行为。比如付费、自己用电子表格重构、主动两次询问、提供个人数据。 需追问的信号：等待名单注册、调研结果、“我聊过的人都喜欢”、投资者兴趣、创始人自身的信念。兴趣不等于需求。
Q2，现状替代方案：“他们现在是怎么解决这个问题的（哪怕方法很糟糕），这个替代方案在时间或金钱上的成本是多少？” 合格答案：具体工具名称、有时间成本的手动流程、部分工作内容就是解决该问题的具体人员。 需追问的信号：“什么都没做，这就是机会所在。”没人费力解决的问题通常是没人真正在意的问题。偶尔这种情况不成立，但此时需要用户解释为什么痛点一直未被察觉。
Q3，极致具象化：“说出具体的人。职位、什么能让他们升职、什么会让他们被解雇。” 合格答案：真实职位和真实激励机制，最好是用户实际交谈过的人。 需追问的信号：只提及细分领域而非具体的人（如“中端市场运营团队”）、虚构的用户画像、同时提及三个不同买家。
Q4，付费决策者与预算：“谁控制这笔预算，他们有没有明确说出愿意支付的金额？” 合格答案：具体的预算负责人、该产品可替代的现有预算项、买家主动提出的金额。 需追问的信号：仅和用户交谈过但付费决策者是其他人；“我们之后再考虑定价”；创始人自己设定的金额。在B2B场景中，喜欢产品的人通常无法批准采购，这种差距导致的失败比需求不足更多。
Q5，最窄切入点：“这个产品最小的可付费版本是什么？要能在本周内让用户付费，而非等平台建成之后。” 合格答案：一个工作流程、一个界面，几天就能完成开发，且有明确的付费用户。 需追问的信号：答案需要依赖平台、集成功能或用户群才有价值。
Q6，观察与意外发现：“你有没有观察过用户独立使用这个产品，有什么意外发现？” 合格答案：现实与预期不符的具体时刻。 需追问的信号：“他们很喜欢”、“没有意外”、仅自己演示过产品。没有意外意味着没有真实观察。
Q7，未来适配性：“如果三年后世界变了，模型成本降低，现有竞品推出了明显的同类功能，这个产品会变得更重要还是更不重要？” 合格答案：需求增长的原因，以及对“为什么现有竞品不直接添加这个功能”的回答。 需追问的信号：只提及增长趋势但无具体机制（如“AI很火”）。惠及所有人的趋势等于没有惠及任何人。

Grading and the verdict bar

评分与结论标准

Grade each dimension you asked about:
  • evidenced. Something that actually happened. A name, a number, an observed behavior, money that moved.
  • asserted. Confident and plausible, but a belief about the world rather than an observation.
  • absent. No answer, a dodge, or the question restated back.
Then the state, in this order of precedence:
  • Contradicted. At least one answer supplies evidence against the idea, not merely missing evidence: nobody works around the problem today, nobody can authorize the spend, the wedge is worthless without the whole platform. This is the strongest thing validatekit can say. Say it plainly.
  • Validated. Demand reality is 
    evidenced
    , and no dimension you asked about is 
    absent
    . Build the wedge.
  • Unproven. Everything else, and the common result. This is not a no; it's an unfinished test. For every 
    asserted
    or 
    absent
    row, name the cheapest experiment that would close it.
If both Contradicted and Validated somehow apply, it's Contradicted, because negative evidence outranks the bar.
The market read doesn't set the state. These three grade founder evidence only, so the state stays defensible against research that turns out to be wrong or stale. A Crowded market alongside 
evidenced
demand is still Validated, and the verdict prose should say the wedge has to survive a specific incumbent at a specific price. Conversely, an Open market never rescues an idea whose founder can't produce a single piece of evidence; a gap in the market is not a customer.
对每个提问维度进行评分：
  • 已证实：实际发生的事情。如具体姓名、数字、观察到的行为、已支付的费用。
  • 主张：自信且合理，但只是对世界的信念而非观察结果。
  • 缺失：无答案、回避问题或重复问题。
然后按优先级得出结论状态：
  • 已否定：至少有一个答案提供了反对该想法的证据，而非仅仅缺失证据：比如现在没人解决这个问题、没人能批准预算、切入点没有平台就毫无价值。这是validatekit能给出的最明确结论。要直白说明。
  • 已验证：需求真实性为
    已证实
    ，且所有提问维度均未出现
    缺失
    。可以开发切入点。
  • 未证实：其他所有情况，也是最常见的结果。这不是“否定”，而是未完成的测试。对于每个
    主张
    或
    缺失
    的项，指出能填补空白的最低成本实验。
若同时满足“已否定”和“已验证”，则结论为“已否定”，因为负面证据优先级高于验证标准。
市场判断不决定结论状态：这三种状态仅基于创始人提供的证据，因此即使调研结果错误或过时，结论仍具有说服力。“拥挤”的市场加上
已证实
的需求仍属于“已验证”，结论措辞应说明切入点需要在特定价格下与特定竞品竞争。反之，“空白”的市场无法拯救创始人无法提供任何证据的想法；市场空白不等于有客户。